Extended depth of field imaging for high speed object analysis

ABSTRACT

A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

RELATED APPLICATIONS

This application is based on a prior provisional application Ser. No.60/748,888, filed on Dec. 9, 2005, the benefit of the filing date ofwhich is hereby claimed under 35 U.S.C. § 119(e) and this application isa continuation of a copending patent application Ser. No. 11/609,269,filed on Dec. 11, 2006, the benefit of the filing date of which ishereby claimed under 35 U.S.C. § 120.

In addition, this application is based on a prior provisionalapplication Ser. No. 60/649,373, filed on Feb. 1, 2005, the benefit ofthe filing date of which is hereby claimed under 35 U.S.C. § 119(e).This application is also a continuation application based on a priorcopending conventional application Ser. No. 11/123,610, filed on May 4,2005, which itself is based on a prior provisional application Ser. No.60/567,911, filed on May 4, 2004, and which is also acontinuation-in-part of prior patent application Ser. No. 10/628,662,filed on Jul. 28, 2003, which issued as U.S. Pat. No. 6,975,400 on Dec.13, 2005, which itself is a continuation-in-part application of priorpatent application Ser. No. 09/976,257, filed on Oct. 12, 2001, whichissued as U.S. Pat. No. 6,608,682 on Aug. 19, 2003, which itself is acontinuation-in-part application of prior patent application Ser. No.09/820,434, filed on Mar. 29, 2001, which issued as U.S. Pat. No.6,473,176 on Oct. 29, 2002, which itself is a continuation-in-partapplication of prior patent application Ser. No. 09/538,604, filed onMar. 29, 2000, which issued as U.S. Pat. No. 6,211,955 on Apr. 3, 2001,which itself is a continuation-in-part application of prior applicationpatent application Ser. No. 09/490,478, filed on Jan. 24, 2000, whichissued as U.S. Pat. No. 6,249,341 on Jun. 19, 2001, which itself isbased on prior provisional patent application Ser. No. 60/117,203, filedon Jan. 25, 1999, the benefit of the filing dates of which is herebyclaimed under 35 U.S.C. §120 and 35 U.S.C. §119(e).

Patent application Ser. No. 09/976,257, noted above, is also based onprior provisional application Ser. No. 60/240,125, filed on Oct. 12,2000, the benefit of the filing date of which is hereby claimed under 35U.S.C. §119(e).

GOVERNMENT RIGHTS

This invention was funded at least in part with grants (No. 9 R44CA01798-02 and 1 R43 GM58956-01) from the National Institutes of Health(NIH) and a contract (NNA05CR09C) from the National Aeronautics andSpace Administration (NASA), and the U.S. government may have certainrights in this invention.

BACKGROUND

Conventional imaging systems are challenged to provide adequatelow-light, high-resolution imaging. Objective components used inhigh-resolution imaging systems need to have very high numeric aperture(NA) values. Unfortunately, a high NA value of the objective componentresults in a very small depth of field in which to view target objects.A small depth of field raises significant challenges in achieving andmaintaining focus of target objects to be viewed during low-light,high-resolution imaging. If focus of a target object is not achieved andmaintained, the resultant defocused image of the target object at adetector is spread over an unacceptably large area of the detector, witha loss in spatial resolution and a decrease in the signal-to-noise ratioassociated with the image of the target object.

Confocal microscopy provides the ability to image cross sections of acell (“optical sectioning”) for the purpose of generating athree-dimensional map of cellular structures, or to synthesize a singletwo-dimensional image in which all cellular structures are in focus.These capabilities are desirable for a wide range of cell analysisapplications, including co-localization studies, quantifying thetranslocation of molecules between cellular compartments, and theenumeration of fluorescence in situ hybridization probes randomlylocated in a nucleus. Although confocal microscopy provides a highlydetailed view of the cell, the repeated scanning required significantlyreduces image acquisition rates, and can in some cases, inducephoto-bleaching of fluorescent probes.

Currently confocal microscopy is limited by the length of time requiredto capture imagery, the types of signals that can be collectedsimultaneously, and the limitation that the cells be immobilized on asolid support. The relatively slow speed of confocal microscopy can be alimiting factor for many applications. Commonly-studied cellularphenomena, including signaling, internalization of surface-boundfactors, chromosomal defects, and various morphological transformations,can be subject to high cell-to-cell variation, occur over a wide andcontinuous range of values, or occur at low frequencies within aheterogeneous mixture of cells. Therefore, the study of such phenomenacan require the observation and analysis of thousands of cells, and theapplication of statistical analysis in order to reach robust andrepeatable scientific conclusions. In such cases, it is oftenimpractical to employ confocal microscopy, due to the low throughput ofthe technique, despite the wealth of information it can provide for eachcell.

In the alternative, conventional fluorescence imaging is generally muchfaster than confocal image stacking and can provide good spatialresolution and fluorescence sensitivity, when employing high NAobjectives. However, conventional fluorescence microscopy is subject toa tradeoff between NA and depth of field. As the NA is increased toimprove light collection and increase spatial resolution, the depth offield is reduced by the square of the NA change. Therefore, images ofweakly fluorescent signals and cellular structures located outside theideal plane of focus can be compromised. This effect is most readilyobserved in experiments employing Fluorescence In Situ Hybridization(FISH) probes that are typically under one micron in size and arecomprised of a limited number of fluorescent molecules, which can bedistributed throughout the nucleus or cytoplasm of a cell. A slightdefocus may preclude the detection of dim probes, or cause multipleprobes located in close proximity to blur into each other. Largeramounts of defocus can cause substantial blur, rendering a FISH spotunrecognizable in an image. These tradeoffs for increased speed over thehighly focused imagery produced by confocal image stacking are generallynot acceptable, given that conventional microscopy, even in automatedform, is still slow compared to flow cytometry. As a result, manystudies of cellular phenomena employ both flow cytometry (for the highthroughput study of large cell populations) and confocal microscopy (forthe detailed imaging of selected individual cells).

The ImageStream™ flow imaging system was developed in part to addressthe gap between the slow, but detailed information obtained by confocalmicroscopy and the fast, but limited cellular information gleaned byflow cytometry. The ImageStream™ system collects six simultaneousmulti-mode images (brightfield, darkfield, and up to four differentfluorescence colors) from cells in flow. High fluorescence sensitivityand resolution are achieved by using 0.75 NA optics and a 0.5 micronpixel size.

Several attempts have been made to extend the depth of field of such aflow imaging system. For example, U.S. Pat. No. 6,583,865 (thedisclosure and drawings of which are hereby specifically incorporatedherein by reference) describes the use of a flow imaging system having atilted detector (or a sample flow path that is tilted relative to thedetector) that effectively increases the depth of field for a moreaccurate enumeration of structures and probes within a cell. Thetechnique can be used in connection with a pulsed light source toproduce multiple images of a moving object at different focal planes, orit can employ a continuous light source to produce a single compositeimage incorporating information from the object at multiple focalplanes. The pulsed light source variant is limited in fluorescencesensitivity because each image has a relatively short signal integrationtime. The continuous light source variant is limited in image qualitybecause the composite image contains both in-focus and out-of-focusinformation at every location in the cell. Hence, there is a need for ahigh speed imaging system having an extended depth of field as well asboth high fluorescence sensitivity and excellent image quality.

U.S. Pat. No. 7,009,651 (the disclosure and drawings of which are herebyalso specifically incorporated herein by reference) describes a flowimaging system in which light from an object is split into a pluralityof optical paths, and one or more of the optical paths are defocusedrelative to the default focal plane of the system, to similarly increasethe depth of field. U.S. Pat. No. 6,211,955 (the disclosure and drawingsof which are hereby also specifically incorporated herein by reference)describes the use of a stereoscopic imaging apparatus to view cells frommultiple angles, for the reconstruction of a three-dimensional (3-D) mapof the cell and accurate enumeration of FISH spots in images. Theeffectiveness of this technique is limited by the depth of field thatcan be achieved with the imaging system. If the depth of field of eachdetector is less than the depth of the cell, or at least, of thenucleus, the spatial resolution of the three-dimensional map produced bythe technique will vary across the cell, and neighboring FISH spots inthe image will blur into each other and be unresolved.

While the ImageStream™ flow imaging system represents a significantadvance over conventional flow cytometry and standard microscopy,demanding applications, such as the quantization of FISH probed cells,require imaging capabilities closer to those achieved by confocal imagestacking.

It would therefore be desirable to develop a flow imaging systemsuitable for high-resolution imagery (0.75 NA and 0.5 micron pixelsize), which also exhibits an extended depth of field.

SUMMARY

This application specifically incorporates by reference the disclosuresand drawings of each patent application and issued patent identifiedabove as a related application.

The concepts disclosed herein enable the depth of field of an imagingsystem to be increased. Such techniques are particularly well suited forenabling flow imaging systems suitable for high-resolution imagery (0.75NA and 0.5 micron pixel size) to achieve extended depth of fieldcellular images similar to those obtained using confocal image stacking.Because flow imaging systems can acquire image data much more rapidlythan confocal microscopy, these techniques will facilitate the analysisof large cellular populations. The concepts disclosed herein furtherencompass imaging systems configured to achieve such extended depth offield imaging.

If the point spread function (PSF) of an imaging system iswell-characterized, the known PSF can be used to improve the spatialresolution of imagery acquired with the imaging system by mathematicallyde-convolving the PSF from the imagery. In the case where object beingimaged lies entirely within the focal plane, only a single image of theobject need be acquired. If the object being imaged is extended in the Zaxis, multiple images of the object must be acquired in different focalplanes order to produce the resolution enhancement, due to uncertaintyabout the focal plane of origin of any given feature within a singleimage of an extended object. However, a single image of an extendedobject can be combined with PSF de-convolution to enhance focus quality(rather than resolution) if the PSF is intentionally modified such thatit is invariant to focal position. The techniques disclosed herein aretherefore based on manipulating an imaging system such that a pointspread function (PSF) of the imaging system is substantially invariantover an extended depth of field. For example, where an unmodifiedhigh-resolution imaging system might exhibit a depth of field of about 1micron, a modified version of the same imaging system might becharacterized as having a PSF that is substantially invariant across adepth of field of about 10 microns. Such a substantially invariant PSFenables the imaging system to integrate light from different focalpositions in object space, making the modified imaging system relativelyinsensitive to defocus. This property, in turn, enables de-convolutionof the PSF to remove the spatial broadening and contrast loss inherentin the unprocessed image, thereby increasing image fidelity and creatingan “in-focus” projected image of the entire cell. The concepts presentedherein combine the above technique for extending depth of field with ameans for greatly increasing detection sensitivity. The increasedsensitivity is important to the practice of extended depth of fieldimaging, because the PSF modification tends to blur optical signals inthe unprocessed imagery, thereby decreasing the signal to noise ratio.Further, the de-convolution process itself tends to amplify noise,reducing the effective signal to noise ratio in the resultant extendeddepth of field imagery, so increasing the signal intensity relative tothe noise is a key feature of the present invention

A key aspect of the concepts presented in the examples discussed hereinis that a wave front of light from the object is deformed, such thatlight from different focal positions is collected. As long as thedeformation process is well understood, processing of the imaging datacollected from the deformed light can correct for errors introduced intothe image data by the deformation process, while enabling theinformation corresponding to the different focal positions to beretained. Thus, after such corrective processing is applied, an imagewith an extended depth of field is obtained.

Thus, the following steps can be considered to be an overview of anexemplary process disclosed herein: providing an imaging system having asubstantially invariant PSF (or modifying an imaging system to achieve asubstantially invariant PSF), collecting image data from an object, andprocessing that image data to achieve an extended depth of field image.De-convolving the image (taking into account the modified PSF) enhancesimage contrast and reduces spatial broadening, thereby improving imagequality.

The concepts disclosed herein encompass several different exemplarytechniques for providing the substantially invariant PSF and thedeformed wave front. As noted above, U.S. Pat. No. 6,583,865 describes aflow imaging system having a tilted image plane (either the detectorbeing tilted or the flow path of the object relative to the detector istilted). Several improvements to that configuration are disclosedherein, including the use of a flow cell having a tilted flow path.Significantly, such an approach does not simultaneously collect datafrom a plurality of different focal positions. Instead, as the objectmoves relative to the tilted image plane, the focal point of the imagingsystem moves to different focal planes in the object. A detectorsynchronized to the motion of the object must be employed (i.e., a timedelay integration (TDI) detector), such that images of the objectobtained at different positions (and at different times) are combined toachieve an extended depth of field image of the object. Rather thanusing such a tilted image plane, an optical element configured to deformthe optical wave front of light from the image can be introduced intothe imaging system between the object and the detector. One advantage tousing an optical element to deform the optical wave front is that lightis simultaneously collected from an EDF in the object. Thus, asynchronized detector is not required (although it may still bedesirable to employ such a detector). Another advantage to using anoptical element to deform the optical wave front is that the element maybe conveniently inserted into or removed from the optical system.Different imaging applications may require more or less depth of field,and having a removable element allows the depth of field to be tailoredto the different applications of the imaging system. A phase plate (anexemplary phase plate can be obtained from CDM Optics of Boulder Colo.,marketed as a Wavefront Coded™ element) represents one type of opticalelement that can be used to deform the optical wave front. Yet anothertype of optical element will deform the wave front by introducing aspherical aberration into light from the object. A separate opticalelement (such as a cover slip) can be used to introduce sphericalaberration, or an existing element in the flow imaging system (such as aflow cell or cuvette, or an objective lens with a correction collar) canbe modified to introduce the spherical aberration. Where the opticalelement is a phase plate or wave front coded (WFC) element, such anoptical element will be disposed in infinite space, otherwise known asaperture space (i.e., behind the objective lens). If the optical elementintroduces spherical aberration, such aberration is preferably inducedbefore light is collected by the aperture of the imaging system (i.e.,between the object or cell being imaged and the objective lens).Essentially, the unmodified imaging system (i.e., the imaging systemwithout the distortion element) is configured to acquire an image of theobject with a relatively narrow depth of field (for example, about 1micron, understanding that such a value is intended to be exemplary, andnot limiting). When the distortion element is introduced into theimaging system, the distortion element induces defocus in the light fromthe object, such that the relatively narrow depth of field is expanded(in an exemplary, but not limiting embodiment, the defocus extends about+/−7 microns beyond the original depth of field); however, such defocus“blurs” the extended depth of field (such blur generally includes bothspatial broadening and a loss of contrast). Post image acquisitionprocessing can minimize the blurring effects of the defocus induced bythe distortion element, enabling an EDF image to be generated. Note thatthe PSF of the imaging system with the distortion element in place isused to facilitate the post image acquisition processing employed toreduce the effects of the defocus induced by the distortion element.

Another aspect of the concepts encompassed herein is directed to a flowimaging system configured to provide the above-described extended depthof field images. Such a flow imaging system will include an opticalelement to deform the wave front of light from the object whileproviding a substantially invariant PSF, a collection element to directlight from the object along an light path, an imaging lens configured toform an image from the collected light, a detector configured to detectthe image and generate image data, and a processor configured to processthe image data (i.e., to de-convolve the image data based on theinvariant PSF) to produce an extended depth of field image of an object.In some exemplary embodiments, the imaging system includes a dispersionelement that disperses the collected light before imaging, and in someexemplary embodiments, the detector is a TDI detector, configured tooutput image data based on a plurality of images of the object detectedover time.

Referring to the ImageStream™ system noted above, the conceptsencompassed herein can be applied to the ImageStream™ system, to enableextended depth of field imaging to be achieved. An ImageStream™ systemmodified for extended depth of field (EDF) image collection can providefor the collection of high-resolution imagery (0.75 NA and 0.5 micronpixel size) without the defocus associated with high NA optics. Suchimagery will have a greatly extended depth of field (a proposed EDFImageStream™ will achieve a depth of field of ten microns, which isapproximately five times the current operating single focal plane depthof less than two microns), allowing for all image features within a 10micron EDF to be clearly in focus. This technology will enable imagingof cellular components having fine structures that are in differentfocal planes (e.g., cytoplasmic proteins, such as actin, microtubules,and sub-cellular organelles (such as mitochondria), cellularmicro-domains (e.g., membrane caps, lipid rafts, proteinco-localization, and signal transduction), and fluorescent in-situhybridization spot counting. Significantly, post-processing of theimagery minimizes the effects of defocus by bringing the entire cellinto focus at the same time. Unlike confocal image stacking techniques,this new methodology and apparatus will operate at hundreds of cells persecond, allowing tens of thousands of cell images to be collected forquantitative analysis in several minutes.

This Summary has been provided to introduce a few concepts in asimplified form that are further described in detail below in theDescription. However, this Summary is not intended to identify key oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

DRAWINGS

Various aspects and attendant advantages of one or more exemplaryembodiments and modifications thereto will become more readilyappreciated as the same becomes better understood by reference to thefollowing detailed description, when taken in conjunction with theaccompanying drawings, wherein:

FIG. 1A is a schematic illustration of an exemplary flow imaging systemfor implementing the concepts disclosed herein;

FIG. 1B is a schematic illustration of an exemplary imaging system forimplementing the concepts disclosed herein, wherein the objected to beimaged are disposed on a plate or slide;

FIG. 1C is a schematic illustration of a readout provided by a TDIdetector employed in an exemplary flow imaging system used in accordwith the concepts disclosed herein;

FIG. 2 is a schematic illustration of an exemplary stereoscopic flowimaging system used in accord with the concepts disclosed herein;

FIG. 3 is a block diagram schematically illustrating the basiccomponents of an exemplary flow imaging system suitable for implementingthe concepts disclosed herein;

FIG. 4 is a block diagram schematically illustrating a method ofproviding extended depth of field imagery for an object;

FIG. 5 schematically illustrates a filter wheel for selectivelypositioning an wave front distortion element in a light path of a flowimaging system, such that the imaging system can be used for both EDFimaging and normal imaging, depending on the position of the filterwheel relative to the light path;

FIG. 6 illustrates a three-dimensional (3-D) contour of an exemplaryoptical element configured to deform the optical wave front of lightfrom an object;

FIG. 7 graphically illustrates the fractional focal offset as a functionof transmission angle due to a glass parallel plate, representinganother type of optical element that can be used to intentionally deformlight from the object;

FIG. 8 schematically illustrates how the PSF of an imaging systemaffects the quality of an image generated by the imaging system;

FIG. 9 schematically illustrates the effect that varying degrees ofdefocus have on an image acquired using a standard non-extended depth offield imaging method;

FIG. 10A graphically illustrates an absolute comparison of through focusmodulation transfer functions, at half the Nyquist frequency, of astandard non-extended depth of field imaging method and a plurality ofextended depth of field (EDF) imaging methods, as disclosed herein, theEDF methods including an exemplary Wave Front Coded (WFC) EDF method, anexemplary Spherical Aberration EDF method, and an exemplary TiltedObject Plane Time Delay Integration (TOPTDI) EDF method;

FIG. 10B graphically illustrates a normalized comparison of modulationtransfer functions of a standard non-extended depth of field imagingmethod (diffraction limited) and the WFC EDF method, the SphericalAberration EDF method, and the TOPTDI EDF method;

FIG. 11A illustrates the best focus imagery obtained using the exemplaryimaging system of FIG. 1A, for both standard imaging and EDF imaging,before processing the image data to correct for errors introduced by thewave front deformation;

FIG. 11B illustrates the best focus imagery obtained using the exemplaryimaging system of FIG. 1A, for various EDF techniques, afterde-convolution;

FIG. 12A illustrates the imagery 5 microns away from the best focusobtained using the exemplary imaging system of FIG. 1A, for bothstandard imaging and EDF imaging, before processing the image data tocorrect for errors introduced by the wave front deformation;

FIG. 12B illustrates the imagery 5 microns away from the best focusobtained using the exemplary imaging system of FIG. 1A, for various EDFtechniques, after de-convolution;

FIG. 13A illustrates a sampling of PSF imagery collected using theexemplary imaging system of FIG. 1A, modified to implement WFC EDFimaging (modified by introducing a phase plate in infinite space);

FIG. 13B illustrates an exemplary de-convolution kernel;

FIG. 14A illustrates the imagery collected using the exemplary imagingsystem of FIG. 1A over a 16 micron focus pan for standard imaging (i.e.,not EDF imaging);

FIG. 14B illustrates the imagery collected using the exemplary imagingsystem of FIG. 1A modified for WFC EDF over a 16 micron focus pan;

FIG. 15A illustrates peak pixel intensity versus object number for imagedata collected by the exemplary imaging system of FIG. 1A operating in astandard mode (i.e., not EDF imaging)) during a step-wise focus pan inwhich approximately 200 objects were imaged at each of nine focuspositions;

FIG. 15B illustrates area versus object number for image data collectedby the exemplary imaging system of FIG. 1A operating in a standard mode(i.e., not EDF imaging) during a step-wise focus pan in whichapproximately 200 objects were imaged at each of nine focus positions;

FIG. 16A illustrates peak pixel intensity versus object number for imagedata collected by the exemplary imaging system of FIG. 1A operating inan EDF mode) during a step-wise focus pan in which approximately 200objects were imaged at each of nine focus positions;

FIG. 16B illustrates area versus object number for image data collectedby the exemplary imaging system of FIG. 1A operating in an EDF mode)during a step-wise focus pan in which approximately 200 objects wereimaged at each of nine focus positions;

FIG. 17A illustrates FISH imagery of cells with disomy for chromosome Ycollected by the exemplary imaging system of FIG. 1A operating in astandard mode (i.e., not EDF imaging);

FIG. 17B illustrates FISH imagery of cells with disomy for chromosome Ycollected by the exemplary imaging system of FIG. 1A operating in an EDFmode;

FIG. 18 graphically illustrates how EDF data collected using theexemplary imaging system of FIG. 1A operating in EDF mode can be used todiscriminate single cells from debris or cell clusters prior toclassifying and enumerating chromosomes;

FIG. 19A graphically illustrates a gray-scale fluorescence image priorto segmentation;

FIG. 19B graphically illustrates a segmentation mask to isolate areas oflocal maxima after initial segmentation;

FIG. 19C graphically illustrates a segmentation mask to isolate areas oflocal maxima after morphology segmentation;

FIG. 20 graphically illustrates an analysis of cellular images obtainedusing the exemplary imaging system of FIG. 1A operating in a standardmode (i.e., not EDF imaging);

FIG. 21 graphically illustrates an analysis of cellular images obtainedusing the exemplary imaging system of FIG. 1A operating in an EDF mode;

FIGS. 22A-22D illustrate randomly selected cell imagery obtained usingthe exemplary imaging system of FIG. 1A operating in a standard mode(i.e., not EDF imaging) and corresponding to “Monosomy Refinement” gates(FIG. 22A), Monosomy false positive events (FIG. 22B), “DisomyRefinement” gates (FIG. 22C), and “Disomy false positive events (FIG.22D); and

FIGS. 23A-23D illustrate randomly selected cell imagery obtained usingthe exemplary imaging system of FIG. 1A operating in an EDF mode andcorresponding to “Monosomy Refinement” gates (FIG. 23A), “Monosomy falsepositive events” (FIG. 23B), “Disomy Refinement” gates (FIG. 23C), and“Disomy false positive events” (FIG. 23D).

DESCRIPTION Figures and Disclosed Embodiments Are Not Limiting

Exemplary embodiments are illustrated in referenced Figures of thedrawings. It is intended that the embodiments and Figures disclosedherein are to be considered illustrative rather than restrictive. Nolimitation on the scope of the technology and of the claims that followis to be imputed to the examples shown in the drawings and discussedherein.

The concepts disclosed herein encompass a method of adding extendeddepth of field capability to a flow imaging system configured forhigh-resolution imagery (exemplary, but not limiting parameters include0.75 NA and 0.5 micron pixel size). It thus should be recognized thatthe term “standard image” or “standard imaging” refers to use of anexemplary flow imaging system (described in detail below) that has notbeen modified for EDF imaging. Such a flow imaging system can combinethe speed, sample handling, and cell sorting capabilities of flowcytometry with the imagery, sensitivity, and resolution of multimodeimagery with an extended depth of field in order to provide acomprehensive feature set to more effectively eliminate artifacts andallow for the complex analysis of the location, distribution, andtranslocation of biomarkers. Standard, non-confocal methods of imagecollection are hindered by extended depth of field limitations. The EDFcapability described herein is a result of modifying an exemplary flowimaging system with an element in aperture space to alter the wave frontin a deterministic way. The combination of a modified wave front andpost-processing of the imagery helps to mitigate the spatial resolutionloss and blurring associated with defocus. The result is a 2-Dprojection of the 3-D cell for each of six multimode images (it beingunderstood that the use of six images are exemplary, and not limiting onthe technique) acquired at rates 100 to 1000 times faster than confocalimage stacking techniques. With the extended depth of field enhancementdisclosed herein, micron-level spatial resolution can be maintained overthe entire cell so that cellular structures and probes lying outside theplane of best focus can be analyzed with greater accuracy, asdemonstrated with empirical FISH probe image data discussed in detailbelow.

More specifically, there are at least four applications in which suchEDF imagery from flow imaging systems can be beneficially employed,including: (1) Cell Activation, such as transcription factor NF-eBnuclear translocation; (2) Mechanisms of Monoclonal Antibody DrugAction, co-localization and compartmentalization; (3) ApoptosisAnalysis: differential rates of apoptosis in heterogeneous cell samples;and, (4) Morphologic cell classification, the identification of cells inblood and bone marrow.

Before discussing the steps employed in one exemplary embodiment forimplementing the present novel approach, it will be beneficial to reviewan exemplary flow imaging system 150 that can be used to execute thismethod. FIG. 1A illustrates the key components of an optical systememployed to project light from objects in flow onto a detector thatemploys an exemplary readout for any type of small object (althoughimaging cells represent an exemplary application). Objects arehydrodynamically focused into a single-file line in a fluidic system(not separately shown), forming a tall but narrow field of view. Thismethod enables the lateral dimension of the detector to be used forsignal decomposition. FIG. 3 is a block diagram showing the majorcomponents of exemplary flow imaging system 150. A key component is adistortion element 152, which is used to distort the wave front of thelight collected from an object, in a predictable and largely reversiblefashion, while expanding the field of view. Referring to FIG. 3, themajor components of a multi-mode EDF flow imaging system include a flowcell or cuvette 151 into which object (such as cells) to be imaged aredirected, an optical distortion element 152 to introduce awell-characterized distortion of light received from the object (suchthat the PSF of the imaging system is substantially invariant over arange of focal planes), collection, dispersing, and imaging opticalelements 153 (to enable the multi-mode imaging such as shown in FIG. 1Ato be achieved), a detector 154 for generating raw image data(preferably, a TDI detector, although other imaging detectors canalternatively be employed, i.e., non-TDI imaging detectors can also beused), and a processor 155 for processing the image data, to enhance theimage data and at least partially correct for the distortions introducedby the distortion element. Such processing can comprise a de-convolutionthat reduces spatial broadening and enhances contrast. It should berecognized that such processing can be implemented using hardware (e.g.,a custom processing circuit or an application specific integratedcircuit (ASIC)), or a combination of hardware and software (e.g., asoftware-driven processor, such as is typically used in a computingdevice, a personal computer being one well-known example thereof). Itshould further be recognized that the distortion element may bephysically located outside of the aperture of the imaging system (i.e.between the flow cell and the imaging objective in the case of thespherical aberration technique), in aperture space after the imagingobjective (in the case of the WFC technique), or may be effected withinthe imaging objective itself by adjustment of an aberration correctioncollar.

Referring now to FIG. 1A, object(s) 99 are hydrodynamically focused in aflow of fluid directed into a flow cuvette 116 and illuminated from oneor more sides using light sources 98 and 100. Light is collected fromthe objects with a high NA objective 102, and the light that iscollected is directed along a light path including lenses 103A and 103B,and a slit 105. A fraction of this collected light is transmitted to anauto-focus subsystem 104 and to a velocity detection system 106. Itshould be noted that in connection with a velocity detection system 106that uses a TDI, it is important to ensure the data signal produced bythe detection system, which is integrated over time to increase thesignal-to-noise ratio, is properly synchronized with the flow of objectsthrough the imaging system. In the context of an exemplaryimplementation, the objects are fluorescently labeled beads orfluorescently labeled cells. The extended depth of field capabilityafforded by the present exemplary technique disclosed herein isparticularly useful in automated chromosome enumeration via FISH probingof Jurkat cells, although such use is intended to be exemplary, ratherthan limiting on the application of this technique.

Either an optical distortion element 5A is disposed between the objectsbeing imaged and the collection lens, or an optical distortion element5B is disposed in infinite space (that is, at the objective aperture orat a conjugate image of the aperture at a subsequent location in theoptical system, but before the detector). Alternatively, opticaldistortion may be introduced via adjustment of a correction collar on anadjustable implementation of objective lens 102. Only one means ofintroducing optical distortion is required. The function of the opticaldistortion is to change the light from the object to achieve a PSF thatis substantially invariant across an EDF, such that negative effects ofthe distortion produced by the element can subsequently be removed bysignal processing, to yield an EDF image.

Yet another technique that can be used to introduce optical distortioninto light from the object is to use a cuvette/flow cell havingdifferent optical thicknesses at different locations, such that imagingthrough the different locations of the cuvette induces different degreesof wave front deformation. For example, different faces of the cuvettecan induce different levels of distortion, with one or more facesintroducing no intentional distortion/deformation, with other facesconfigured to intentionally deform the optical wave front of light fromthe object. Moving the cuvette relative to the imaging optical enablesthe deformation to be selectively induced. An optional cuvettemanipulator 9 for manipulating the position of the cuvette relative tothe optical system is shown in FIG. 1A. Where different faces of thecuvette induce different levels of deformation, such means willgenerally rotate the cuvette. It should also be recognized that a singleface of a cuvette can induce different levels of deformation atdifferent locations, such that translating the cuvette linearly caninduce different levels of deformation. In such an embodiment,manipulator 9 will be configured to translate the cuvette linearly.Those of ordinary skill in the art will recognize that many differentstructural configurations can be used to implement manipulator 9, suchas stepper motors, linear actuators, hydraulics, powered hinges, poweredlinkages, and others. The specific configuration is not critical, solong as manipulation of the cuvette does not introduce additionaloptical errors beyond the intentional deformation, thus the specifiedstructures for manipulator 9 should be considered exemplary, rather thanlimiting.

The majority of the light is passed to a spectral decomposition element108, which employs a fan-configuration of dichroic mirrors 110 to directdifferent spectral bands laterally onto different regions of a TDIdetector 114. Thus, the imaging system is able to decompose the image ofa single object 118 into multiple sub-images 120 across detector 114,each sub-image corresponding to a different spectral component. In thisview, detector 114 has been enlarged and is shown separately tohighlight its elements.

Spectral decomposition greatly facilitates the location, identification,and quantification of different fluorescence-labeled biomolecules withina cell by isolating probe signals from each other, and from backgroundauto fluorescence. Spectral decomposition also enables simultaneousmultimode imaging (brightfield, darkfield, etc.) using band-limitedlight in channels separate from those used for fluorescence imaging.FIG. 1A illustrates an exemplary flow-based embodiment of flow imagingsystem 150. However, it should be recognized that such an imaging systemcan be configured to collect images of objects on a plate or slide 7,where the plate/slide moves relative to the imaging system, instead ofthe flow-based embodiment, as indicated in FIG. 1B.

It should be recognized that other elements (such as a prism or a filterstack) could be similarly employed to spectrally disperse the light, andthe dichroic mirrors simply represent an exemplary implementation. Flowimaging system 150 can employ a prism (not shown) or a grating orientedto disperse light laterally with regard to the axis of flow prior to thefinal focusing optics, for spectral analysis of each object's intrinsicfluorescence. In yet another exemplary embodiment of a suitable flowimaging system that is contemplated (but not shown), a cylindrical finalfocusing lens can be employed to image a Fourier plane on the detectorin the cross-flow axis, enabling analysis of the light scatter angle.These techniques for multi-spectral imaging, flow spectroscopy, andFourier plane scatter angle analysis can be employed simultaneously bysplitting the collected light into separate collection paths, withappropriate optics in each light path. For enhanced morphology or toanalyze forward scatter light, a second imaging objective and collectiontrain can be used to image the particles through an orthogonal facet ofthe flow cuvette 116, thereby viewing the objects in stereoscopicperspective with no loss of speed or sensitivity.

To analyze the collected imagery, a software based image analysisprogram can be employed. One example of suitable image analysis softwareis the IDEAS™ package (available from Amnis Corporation, Seattle,Wash.). The IDEAS™ software package evaluates over 200 quantitativefeatures for every cell, including multiple morphologic and fluorescenceintensity measurements, which can be used to define and characterizecell populations. The IDEAS™ software package enables the user to definebiologically relevant cell subpopulations, and analyze subpopulationsusing standard cytometry analyses, such as gating and backgating. Itshould be understood, however, that other image analysis methods orsoftware packages can be employed to apply the concepts disclosedherein, and the IDEAS™ image analysis software package is intended to bemerely one example of a suitable software for this purpose, rather thanlimiting on the concepts disclosed herein.

Turning now to FIG. 1C, detector 114 of the exemplary flow imagingsystem shown in FIG. 1A is implemented using a TDI that performs highthroughput imaging with high sensitivity. As shown in an exemplaryreadout 138, the image on the TDI detector is read out one row of pixelsat a time from the bottom of the detector. After each row is read out,the signals in the remaining detector pixels are shifted down by onerow. The readout/shift process repeats continuously, causing latentimage 142 to translate down the detector during readout (note themovement of latent image 142 through frames T1-T6). If the readout rateof the TDI detector is matched to the velocity of the object beingimaged, the image does not blur as it moves down the TDI detector. Ineffect, the TDI detector electronically “pans” the rate at which rowsare read out to track the motion of an object being imaged. To provideoptimum results for this technique, it is important to accuratelymeasure the velocity of the objects being imaged and to employ thatmeasurement in feedback control of the TDI readout rate. Thus, accuratevelocity detection for objects moving in flow enables the TDI imaging tobe implemented properly.

One primary advantage of TDI detection over other methods is the greatlyincreased image integration period it provides. An exemplary flowimaging system used in connection with the present invention includes aTDI detector that has 512 rows of pixels, provides a commensurate 512×increase in signal integration time. This increase enables the detectionof even faint fluorescent probes within cell images and intrinsic autofluorescence of cells acquired at a high-throughput.

Furthermore, the use of a TDI detector increases measured signalintensities up to a thousand fold, representing over a 30 foldimprovement in the signal-to-noise ratio compared to other methodsdisclosed in the prior art. This increased signal intensity enablesindividual particles to be optically addressed, providinghigh-resolution measurement of either scattered spectral intensity ofwhite light or scattered angular analysis of monochromatic light ofselected wavelengths.

Exemplary flow imaging system 150 can be configured for multi-spectralimaging and can operate with, for example, six spectral channels: DAPIfluorescence (400-460 nm), Darkfield (460-500 nm), FITC fluorescence(500-560 nm), PE fluorescence (560-595 nm), Brightfield (595-650 nm),and Deep Red (650-700 nm). The TDI detector can provide 10 bit digitalresolution per pixel. The NA of the exemplary imaging system istypically about 0.75, with a pixel size of approximately 0.5 microns.However, those skilled in the art will recognize that this flow imagingsystem is neither limited to six spectral channels nor limited to eitherthe stated NA, or pixel size and resolution.

While the elimination of focus variation in a 2-D projection of a cellwill likely be beneficial in many applications, it may be limiting inothers, such as co-localization assays. This possibility was a keyconsideration in the utilization of a phase plate for the WFC EDFmethodology, because the WFC EDF method can be implemented to providedifferent levels of distortion, or disabled completely, by removing orsubstituting optical elements in the system's aperture plane.

Another exemplary flow imaging system embodiment is a stereoscopicarrangement, as illustrated in a flow imaging system 70 of FIG. 2,wherein fluid flow 22 entrains object 99 (such as a cell, butalternatively, a small particle) and carries the object through flowimaging system 70. Light 30 from object 99 passes through collectionlens 32 that collects the light, producing collected light 34, which isapproximately focused at infinity, i.e., the rays of collected lightfrom collection lens 32 originating at the same location in the objectare generally parallel. Collected light 34 enters a prism 36, whichdisperses the light, producing dispersed light 38. The dispersed lightthen enters imaging lens 40, which focuses light 42 onto TDI detectors114 a and 114 b. As noted above, either optical distortion element 5A or5B or adjustable objective lens 102 (or a cuvette/flow cell configuredto introduce optical distortion) is included along the optical pathbetween each the object being imaged and the detector. It will typicallybe desirable to use the same type of optical distortion technique ineach optical leg; however, it should be recognized that differentdistortion techniques can be implemented in each leg, so long as eachsignal from each detector is processed appropriately to correct for theintentional distortion in each optical leg.

The use of two different optical legs enables the object to be imagedfrom two different directions, in order to distinguish features thatwould otherwise overlap when viewed from a single direction. While thisembodiment can also be employed for objects on moving substrates, suchas microscope slides, it is particularly useful for analyzingmulti-component objects in solution flowing through the system, such ascells containing FISH probes. Such probes appear as point sources oflight anywhere within the cell's 3-D nucleus. In some cases, two or moreFISH probes may appear in an overlapping relationship along the opticalaxis of the imaging system. In such cases, one of the FISH probes mayobscure the others, making it difficult to determine the number ofprobes present in the cell. This factor is important in thedetermination of genetic abnormalities such as trisomy 21, otherwiseknown as Down syndrome. Single-perspective systems may address thisproblem by “panning through” the object along the optical axis toacquire multiple image planes in the object. While this method may beeffective, it requires a significant amount of time to collect multipleimages and cannot be readily applied to a cell in flow. The stereoscopicimaging system 70 in FIG. 2 includes two TDI detectors 114 a and 114 b,and their associated optical components, as discussed above, inconnection with flow imaging system 150.

By positioning the optical axes of collection lenses 32 for the two TDIdetectors so that they are disposed at an angle to each other, forexample, about 90 degrees, it is possible to separately resolve the FISHspots imaged from two or more FISH probes on at least one of TDIdetectors 114 a or 114 b. If two or more FISH probes overlap in regardto the image produced on one of the detectors, they will be separatelyresolved in the spectrally dispersed images produced on the other TDIdetector. Further, the use of two TDI detectors in flow imaging system70 in what might be referred to as a “stereo or three-dimensionalconfiguration” provides flexibility in the configuration of each leg ofthe system, including parameters such as the relative TDI readout rates,axial orientations, inclinations, focal plane positions, andmagnification. Multiple cells or other objects may be imaged onto eachdetector simultaneously in the vertical direction. Since the objectsmove in synchronicity with the signal on the TDI, no gate or shutter isrequired to prevent blurring of the image. A pulsed or CW light source(without the need for a trigger mechanism to time a pulse coincidentwith particle arrival in the field of view) is employed. If a pulsedlight source is used, the extended field of view in the axis of motionassociated with TDI detection enables the cell or object in motion to beilluminated by multiple light pulses during its traversal through theimaging system. In contrast to a frame-based imaging apparatus, a TDIsystem can produce a single un-blurred image of the object thatintegrates the signal from multiple light pulses. When a CW light sourceis used, the signal generated by the object will be collected throughoutthe entire traversal of the object through the field of view, ratherthan only a small segment in time when a shutter is open. Therefore, theamount of signal collected and imaged on the detector in this exemplaryembodiment is substantially greater than that of the prior artframe-based imaging systems. Consequently, the present approach canoperate at very high throughput rates with excellent signal-to-noiseratio.

Application of the optical system shown in FIG. 1A in an orthogonalconfiguration as shown in FIG. 2 provides the ability to determine thelocation of a source of light within the cell in three dimensions. Asingle axis EDF system projects light from the cell onto a twodimensional plane without the blur associated with defocus. Therefore,in X-Y-Z Cartesian space, one can readily determine, for example, thelocation of light coming from the cell in the X and Z axes, assuming theoptic axis is parallel to the Y axis. In the Y axis no positionalinformation is available. However, if a second EDF optical system ispositioned orthogonal to the Y axis and parallel to the X axis, one canfurther determine the location of light coming from the cell in the Yaxis. A point of light coming from a cell will be imaged onto twodetectors simultaneously. Since both detectors collect light from thesame Z axis, the Z location of the light on the detectors provides areference with which to correlate the position of light in all threeaxes. To unambiguously determine the X, Y and Z location of a point oflight, one need only locate the light in the Z axis in the appropriatechannel on both detectors, 114 a and 114 b, and then assess the positionof the light in the X and Y axes on the corresponding detector. For anapplication involving multiple discrete sources of light within thecell, such a FISH spot enumeration, the techniques disclosed herein maybe used to unambiguously count spots from the cell. For molecularco-localization analyses, the same methodology can be applied. However,in this case each molecular species is tagged with a different colormarker. Therefore, the same process is applied in two channels of thedetector. Since each channel is spatially registered with the other, onecan compare the location of light in each channel to assessco-localization of two different molecular species.

Beyond unambiguously locating the position of discrete sources of lightfrom the cell, the concepts disclosed herein can also be used toreconstruct 3-D models of solid bodies and surfaces within the cell.This can be accomplished by dividing the volume of the cell into a setof voxels with a dimension is each axis equal to the pixel size in eachaxis on the detectors. The intensity of each voxel in the volume can bedetermined in stepwise fashion. On a given detector, a single pixel, inthe X-Z plane for example, represents the sum of voxel intensities forall voxels at that X-Z location along the Y axis. Therefore, todetermine the signal in each voxel along the Y axis (at that X-Zlocation), the total signal from the X-Z pixel would be apportioned intoeach voxel along the Y axis in accordance with relative proportion ofsignal present in each pixel along the corresponding row on the Y-Zdetector. For example, the signal for an arbitrary set of voxels,X3Z5Y1, X₃Z₅Y₂, X₃Z₅Y₃, X₃Z₅Y . . . , X3Z5Y100, could be determined asfollows. The signal for pixel X₃Z₅ in the third column and fifth row ondetector X-Z would contain the sum of the signal for all voxels listedabove. If this sum were 1000 counts and all 100 pixels on the fifth rowof the Y-Z detector contained the same value, than the 1000 count signalwould be distributed evenly among all voxels listed. If for example,only the 10^(th) and 11^(th) pixels contained signal, then all voxelsignal levels would be set to zero except for voxels X₃Z₅Y₁₀ andX₃Z₅Y₁₁. The 1000 count signal would then be distributed into thosevoxels accordance with the relative signal levels in pixels 10 and 11 onthe fifth row of detector Y-Z. In this manner all voxels throughout thevolume of a cell could be assigned signal levels to construct a 3-Dmodel of the cell. This model could then be viewed from any angle, andsliced along arbitrary planes, to better visualize the spatialarrangement of cellular components and molecules contained within acell.

Also illustrated in FIG. 2 are several exemplary positions for lightsources, which are useful for different purposes in connection with flowimaging system 70. Light sources are disposed so that light 58 emittedfrom the source travels toward the object in a direction that isgenerally aligned with the optical axis of collection lens 32, and theimage formed on the TDI detectors thus will not include light absorbedby object 99. Light absorption characteristics of the object can bedetermined by illuminating the object using these light sources. Morespecifically, in connection with TDI detector 114 a, light source 62provides illumination of object 99 from a direction so that absorptioncharacteristics of the object can be determined from the image producedon the TDI detector. At the same time, light provided by light source 62that is scattered from object 99 can be used to produce a scatter image,and spectrally dispersed images on TDI detector 114 b. Light source 74can be employed to produce spectrally dispersed and scattered images onboth TDI detectors 114 a and 114 b. If light sources 62 and 72 are ofdifferent wavelengths and an appropriate filter is provided to block thewavelength from the light source aligned with the optical axis ofrespective collections lenses 32, these two light sources can be usedfor producing scattered light from the object. For example, supposelight source 72 produces light of a wavelength A that scatters fromobject 99 and is directed toward TDI detector 114 a. By including afilter (not shown) that blocks a wavelength B produced by light source62, the light at wavelength B will not directly affect the imagesproduced on TDI detector 114 a. Similarly, the light from light source72 would be blocked with an appropriate filter (not shown) so that itdoes not interfere with the imaging of light produced by light source 62that is scattered from object 99 onto TDI detector 114 b.

Epi light source 66 is also illustrated for use in producing images onTDI detector 114 a in connection with partial reflector 68. Light source64 can be used to generate reflected light to produce images on TDIdetector 114 a, while scattered light from this source is directedtoward TDI detector 114 b. These and other possible locations of lightsources will be apparent to those of ordinary skill in the art, asappropriate for providing the incident light on the object needed toachieve imaging, depending upon the particular application andinformation about the object that is desired. Moreover, if the WFC EDFmethod that is described below in detail is applied to both legs of flowimaging system 70, an accurate 3-D map of the cell can be reconstructed.

While the system of FIG. 2 can be employed to acquire non-EDF images(i.e., it can be used without optical distortion elements 5A or 5B, oradjustable objective 102 or cuvette or cover slip configured tointroduce optical distortion), the use of such elements and thepost-image processing to partially correct for such distortion enablesstereoscopic high definition EDF imaging to be acquired from objects inflow, thereby enabling a large amount of image data to be acquired for alarge number of objects much more rapidly than is possible usingconfocal microscopy.

Extended Depth of Field Imaging

EDF as used herein refers to the capability of imaging more parts of anobject in focus than could be imaged using an unmodified imaging system(i.e., an imaging system not modified to achieve the EDF imaging). SuchEDF imaging can enable all cellular components within a ten micron orgreater depth of field to be imaged in focus. EDF cellular imagingoffers an alternative method to developing a confocal-like imageprojection with the entire cell in focus simultaneously. One of theissues raised by single-plane image capture of microscopic objects isthe effect of focus variations on the quality of captured imagery. Inparticular, if the object to be imaged has fine structures, which areintrinsically in different focal planes, it is not possible to resolveall of the corresponding fine detail in a single planar image. The finerthe details to be imaged, the more important this problem becomes,because the size of the smallest features that can be resolved variesinversely with the NA of the optical system, while the depth of focusshrinks faster, as the inverse square of the NA. Thus, EDF imaging canbe accomplished at very high speed and eliminates the photo bleachingeffects associated with repeated acquisitions of the cell imagery atdifferent planes of focus. EDF imaging can be accomplished in severalways. However, the underlying principal involves the formation of a PSFthat is invariant over an expected range of focal positions. For mostcell imaging applications, this range is approximately 15 microns. Theprocess of achieving a PSF invariant to focal position increases thesize and changes the character of the PSF when compared to the classicalbest focus point spread. The increased size reduces the ability of theoptical system to generate contrast and resolve image detail. However,through de-convolution, the contrast can be largely restored with thebenefit of providing “best-focus-like” resolution over a greatlyenhanced focal range. The end result is a high-resolution image of thecell with all features simultaneously in focus.

The concepts disclosed herein encompass at least three methods toachieve focus invariant PSFs: (1) a WFC EDF method using a phase plate,for example, a WAVE FRONT CODED™ element provided by CDM Optics, Inc. ofBoulder, Colo.; (2) a Spherical Aberration EDF method; and, (3) a TiltedObject Plane Time Delay Integration (TOPTDI) EDF method. Basicprinciples relating to the TOPTDI EDF method are described in U.S. Pat.No. 6,583,865. The present discussion briefly covers improvements to theTOPTDI method. It should be noted that the WFC EDF technique and theSpherical Aberration EDF technique can be distinguished from the TOPTDIEDF technique, in that the TOPTDI EDF technique acquires data fromdifferent focal planes at different times, and thus requires a TDIdetector. The WFC EDF technique and the Spherical Aberration EDFtechnique acquire EDF data simultaneously, and a TDI detector is notrequired. Use of a TDI detector in implementing the WFC EDF techniqueand the Spherical Aberration EDF technique is desirable, because the TDIdetector increases the amount of light (and therefore data) that can becollected from any object, thereby improving the signal-to-noise ratioof the image; however, each different image acquired by the TDI detectorincludes an EDF before the integrated image is provided by the detector,in contrast to the TOPTDI implementation.

In summary, all three methods result in a PSF that integrates light fromdifferent focal positions in object space, making it relativelyinsensitive to defocus. This property, in turn, enables de-convolutionof the PSF to remove the spatial broadening and contrast loss inherentin the unprocessed image, thereby increasing image fidelity and creatingan “in-focus” projected image of the entire cell. However, only the WFCEDF method allows for directed tuning of the optical wave front tooptimize the PSF for EDF imaging.

FIG. 4 is a block diagram illustrating the method of providingmulti-mode extended depth of field imagery for an object. At a step 160,the method begins with deformation of the optical wave front of lightfrom an object as shown in a step 162. As discussed below in detail, theoptical wave front may be deformed by one of a phase plate configured toinduce a phase change to light passing through the phase plate, anoptical element configured to induce a phase change or distortion tolight passing through the optical element, an adjustable objective lens,or a cuvette having different thicknesses at different locations throughwhich the object can be imaged (in at least one embodiment, thecuvette/flow cell includes a face configured to induce distortion, and aface that does not induce distortion, such that rotating the cuvetterelative to the imaging optics enables the distortion to be selectivelyinduced). This deformation is performed in such a way that a PSF doesnot vary substantially across an extended depth of field. Some cellularobjects have fine structures that are in different focal planes, and theapplication of the deformation of the wave front enables all imagefeatures within the extended depth of field across the different focalplanes to be clearly in focus (at least after image processing hasreversed the distortion effects), because the deformation defocuses andexpands the depth of field, thereby enabling light from the differentfocal planes to be simultaneously collected. The method continues in astep 163, wherein the deformed or modified light is dispersed into aplurality of different light beams. Such spectral dispersion enables adispersed image (or a plurality of spectrally distinct images) of theobject to be acquired, generally as indicated in FIG. 1A. An imaginglens is used to generate a dispersed image (or a plurality of images) ofthe object in a step 164, and the dispersed image is detected in a step166. The detector of FIG. 1A can thus generate either a plurality ofdifferent spectral images (one image per channel), or a single dispersedimage (comprising a plurality of spectrally dispersed images).

Optional step 168 indicates that the next step is to determine the PSFof the imaging system that produced the deformed optical wave front.While this step is required to process the raw image data to generatethe best quality EDF image, it should be recognized that such a step maynot be implemented by a user in some imaging systems, since it could beimplemented by a manufacturer of the imaging system, and stored as aknown parameter (thus the arrow from step 168 to start). The PSF of theimaging system including the optical distortion element need only bedetermined once, as long as the configuration of the imaging systemremains unchanged. Once a change is made to the optical configuration ofthe imaging system that changes the imaging system's inherent PSF, thePSF for the modified system would need to again be determined. In a step170, the image data can be de-convolved using the PSF to reduce negativeeffects of the wave front distortion. Then, the extended depth of fieldimage for the object can be produced in a step 172, and the method iscomplete as shown in a step 174.

Simulation of the WFC EDF Method

The WFC EDF method involves imparting a deformation in the optical wavefront of the object via the addition of an optical or distortion elementsuch as a phase plate (or preferably the WAVE FRONT CODED™ elementprovided by CDM Optics, Inc. of Boulder, Colo.) in the aperture plane ofthe optical system. The deformation causes light from different focalplanes corresponding to a single lateral position in object space to beimaged on the detector plane simultaneously. A significant advantage ofthe WFC EDF method over the TOPTDI EDF method is the ease with which thesystem can be converted from standard imaging to EDF imaging. Theconversion requires the insertion of the WFC element in the aperturespace of the system. The exemplary flow imaging system was designed toplace an external image of the aperture in an easily accessiblelocation. For example, a six-position software controlled aperture wheel157 is shown in FIG. 5, which can be readily disposed in the exemplaryimaging system between the objective and the detector. In an exemplaryembodiment, the position of the filter wheel can be controlled remotely,so that the internal components of the imaging system do not need to beaccessed to selectively switch the imaging system between a standardimaging mode and an EDF imaging mode. Of course, the image processingrequired in standard mode and EDF mode will be different.

In order to simulate the WFC EDF method, a phase plate was modeled andconsists of an optically clear element having a two-axis cubic waveform,where the axes cross orthogonally. A phase plate is an optical componentof transparent material placed in the aperture space of an opticalsystem. The phase plate is optically clear and has slight variations inits thickness in order to retard or advance the phase of the wave frontrelative to the un-deviated wave front. CDM Optics, Inc. has developedthe ability to construct phase plates with arbitrary surface shapes andmicron-level fabrication tolerances. These phase plates can be used toinduce deformations in the optical wave front to potentially provide amore consistent PSF through an extended focal range. Thus, the slightvariations in thickness across the plate's surface serve to retard oradvance the phase of the wave front. From a geometric perspective, theangular changes in the surface of the element cause ray paths to deviatefrom their original course to image light from different points alongthe optic axis for a given lateral position in the image plane. For thissimulation, an element was modeled with a sag of the form shown inEquation 1, where n=3.

$\begin{matrix}{{Sag} = {\sum\limits_{n = {\lbrack{3,7,9}\rbrack}}\; {a_{n}\left( {\left( \frac{x}{r_{0}} \right)^{n} + \left( \frac{y}{r_{0}} \right)^{n}} \right)}}} & (1)\end{matrix}$

A coefficient a_(n)=0.000122 was selected to generate approximately fivewaves of peak to valley wave front error over the aperture. The elementshown as a 3-D rendering in FIG. 6 contains about 6.6 microns of totalsag. The element was modeled at an exposed aperture stop in theexemplary flow imaging system to generate the PSFs used in thesubsequent analysis as described below. The results are summarized inFIGS. 10A and 10B, described in detail below.

Simulation of the Spherical Aberration EDF Method

The spherical aberration EDF method involves imparting sphericalaberration in the wave front by inserting a distortion element betweenthe object and the objective lens in order to induce sphericalaberration into the collected imagery. Useful distortion elementsinclude a cover slip (or parallel plate), a custom objective with acorrection collar, a custom cuvette having different optical propertiesin different parts of the cuvette, and switchable optical elements inthe image collection path. Spherical aberration causes different regionsin the aperture to focus at different points along the optical axis sothat points from multiple focal planes in object space are imaged ontoone detector plane.

Prior to providing a more detailed discussion of the more completesimulations of the optical system performed with the parallel plate inplace, it may first be helpful to present an approximate calculation ofthe effect of the introduction of a parallel plate of glass on thevariation of the focal positions of light entering a microscopeobjective. Assume that there is a passage of a ray of light R from anobject 0 through a parallel plate of glass of thickness t. The ray Rleaves the object 0 at an angle Θ to the optical axis. As shown inEquation 2, it is bent according to Snell's Law to an angle φ:

$\begin{matrix}{\varphi = {\sin^{- 1}\left( \frac{\sin \; \Theta}{n} \right)}} & (2)\end{matrix}$

where n is the refractive index (approximately 1.5) inside the glass.

Upon leaving the glass, it is bent back to its original angle. Whileinside the glass, as shown by Equation 3, it has traveled a distance yfurther from the optical axis than it was at its entry point:

$\begin{matrix}{y = {{t\; \tan \; \varphi} = {t\; {{\tan \left\lbrack {\sin^{- 1}\left( \frac{\sin \; \Theta}{n} \right)} \right\rbrack}.}}}} & (3)\end{matrix}$

Tracing the exiting ray R back to where it appears to originate on theoptical axis, Equation 4 shows that the focal displacement z′ due to thepresence of the glass plate is:

$\begin{matrix}{z^{\prime} = {t - {\frac{y}{\tan \; \Theta}.}}} & (4)\end{matrix}$

One useful limit to consider is the case when Θ is very small. In thiscase it can be shown that:

$\begin{matrix}{{\begin{matrix}\lim \\\left. \Theta\rightarrow 0 \right.\end{matrix}z^{\prime}} = {{t\left( {1 - {1/n}} \right)}.}} & (5)\end{matrix}$

The spherical aberration of the optical system is caused by the factthat z′ does not remain constant as Θ ranges from zero up to the NA ofthe microscope objective, which represents the largest angle ray theobjective will accept. The objective used in the exemplary flow imagingsystem has an NA of 0.75.

FIG. 7 shows the fractional focal offset z′/t as a function of Θ,assuming a nominal glass refractive index n of 1.5. Along the opticalaxis, z′/t is about 0.33, while at the maximal angle for an NA of 0.75(the NA of the exemplary flow imaging system), z′/t is about 0.49. Thedifference between these two fractional focal displacements isapproximately 0.16. To set this fractional difference equal to a 10micron focal depth would require a glass thickness of 1010.16=63microns. In this experiment, such a thin slip of glass was not readilyavailable, and instead, a commercially available 110 micron thick coverslip was used. The focal offsets introduced by this cover slip variedover a range of 17 microns, which is larger than ideal for covering thedepth of a cell nucleus, but still well in the useful range forexperimentation.

Now, returning to the simulation, a desirable feature of the SphericalAberration EDF method capability is selectability, where the sphericalaberration can be introduced or not, depending upon the requirements ofthe particular assay that is being run. The EDF algorithm can then beapplied only to imagery collected with the EDF hardware in place. Aselectable EDF can be achieved in a number of ways in hardware. First,an insertable cover slip can be disposed between the objective and thecuvette. In an empirical study, the cover glass was held in place on theface of the cuvette by a drop of alcohol to form a temporary rigidoptical contact. The introduction of the cover glass creates a knownaberration in the optical system, known as spherical aberration. Inbrief, spherical aberration causes light rays departing a single sourceat different angles relative to the optic axis to focus at differentpositions along the optic axis. The immediate result is that imagerybecomes more fuzzy. A more subtle effect is that the imagery is lessdependent on the exact focal position of the lens relative to thesource. If the imagery is enhanced digitally to reduce the fuzziness viade-convolution, while preserving the independence from focal position,an instrument with enhanced depth of field is achieved, at the cost oflosing some of the signal-to-noise ratio characteristic of in-focus datafrom the original instrument. Issues include precision motionrequirements and the need to establish and maintain precise angularalignment of the cover slip surfaces orthogonal to the optical axis inthe very limited working distance (0.5 mm) between the cuvette andobjective available in the exemplary imaging system.

In another Spherical Aberration EDF embodiment, a custom objective witha motorized spherical aberration correction collar can be utilized.Potential problems with such an embodiment include the need to provide acustom optical design, and development of the objective lens and themechanical interface to drive the correction collar.

In a further Spherical Aberration EDF embodiment, a custom cuvette withdifferent optical thicknesses may be presented to the image collectionoptical path. Issues with such an embodiment include tight fabricationtolerances on the cuvette wall thicknesses and face perpendicularity,precision motion control within the optical alignment requirements, aswell as maintenance of the interface to the fluidic system in the flowcell/cuvette assembly.

In yet another exemplary Spherical Aberration EDF embodiment, switchableoptical elements in the image collection optical path may include thefinal focus lens to the camera/detector, which can be designed withresidual spherical aberration and disposed in place of the standardfocusing lens during EDF imaging. Issues include the optical design andfabrication of the spherically aberrated lens to maintain parfocalitywith the standard lens and the motion control system for swapping thelenses in the optical path.

Varying degrees of spherical aberration were modeled to determine thebest trade off between contrast loss and depth of field expansion.Evaluation of the PSFs at various focal positions provides a qualitativeunderstanding of the limitations of the Spherical Aberration method.Ideally, the PSF would remain fairly consistent over the focal range ofinterest. To simulate the Spherical Aberration EDF method, the exemplaryflow imaging system was modeled with a decreased flow cuvette thicknessto add 1.8 waves of peak-to-peak spherical aberration after refocusing.This optical configuration was then used to model the PSF at the variousfocus locations required for subsequent analysis. The results aresummarized in FIGS. 10A and 10B, described in detail below.

Simulation of the TOPTDI EDF Method

The TOPTDI EDF method can be employed in concert with the TDI detectionmethods used in the exemplary flow imaging system described in U.S. Pat.No. 6,583,765, the drawings and specification of which are herebyspecifically incorporated herein by reference. In this method, theobject plane (or detector plane) is tilted such that during the imageintegration process, the cell scans through a continuous range of focuspositions. In other words, the focal plane is tilted relative to theaxial flow of the cells such that light from multiple focal planes inobject space is integrated during image collection. Either the detectorcan be tilted relative to a non-tilted flow path for objects beingimaged, or a cuvette with a tilted flow path and means for opticallycorrecting for the coma and astigmatism that will be introduced by thetilted reflective surface of the cuvette wall and air interface can beused. In addition, a custom-designed cuvette that has a tilted channelcan be employed, thereby eliminating the concern with respect to theastigmatism and coma by ensuring that the cuvette is orthogonal to thecollected light. Only the water/glass cuvette is non-orthogonal,providing a decrease in optical aberrations. Introduction of an opticalcomponent such as an optical wedge, which effectively tilts the imageplane with respect to the camera, may also be utilized. Alternatively, aconvolution filter can be used in the beam path, and the knownde-convolution algorithm may be utilized to correct for the astigmatismand coma effects.

The technique of modeling a tilted detector methodology to implement areal time “pan through” of focal planes for each object during the TDIintegration distance showed potential; however, empirical studiesindicated it requires more than a 45 degree tilt of the detector forless than 7 microns of pan through. In addition to implementationdifficulties, this degree of tilt induced an anamorphic pixel aspectratio and decreased collection efficiency. Further empirical studieswere performed to investigate tilting the object plane less than thethree degrees, in order to pan through 10 microns of focal positions.Unfortunately, initial modeling studies indicated that three degrees oftilt at the air glass interface of the cuvette imparted an unacceptableamount of coma and astigmatism to the wave front.

As an alternative, an improved implementation of the tilted-planemethodology has been developed to achieve the desired EDF performance,without the introduction of excessive off axis aberrations. This methodutilizes optical fabrication techniques developed for precision prismmanufacturing, to polish the desired tilt angle into the cuvette frontsurface, relative to the cuvette flow channel, which enables theair/glass interface to remain orthogonal to the objective optical axis,while the three degree tilted surface is placed at the glass/waterinterface, thereby substantially reducing the residual coma andastigmatism, since the index or refraction mismatch is reduced. ThisTOPTDI system was modeled, and PSFs were determined for the matrix offield heights and shifted object positions shown below:

Object Field Height Object Shift Object Shift Object Shift (um) BestFocus +5 um Best Focus Position Best Focus −5 um 128 +10 +5 0 85.3+8.332 +3.332 −1.668 42.7 +6.668 +1.668 −3.332 0 +5 0 −5 −42.7 +3.332−1.668 −6.668 −85.3 +1.668 −3.332 −8.332 −128 0 −5 −10

Using the individual PSF from each row within a given column in thematrix above, a PSF was synthesized for a given TOPTDI integration path.These PSFs were then used to compute the through focus MTF plots for thecomparison of methodologies. The results are summarized in FIGS. 10A and10B, as described in detail below.

Processing of Raw Image Data to Produce the Extended Depth of FieldImage

Within limitations, the blur associated with the wave front distortioninherent in EDF imaging can be removed through post-processing of theimage using de-convolution. De-convolution is the process of enhancingthe contrast of a system over some range of frequencies, usually withthe objective of overcoming some degradation that has occurred inproducing the image data. The difficulty with this procedure is thatnoise, which is often present at those frequencies, is amplified alongwith any real signal that may be present. Because of this difficulty, itis usually not desirable to attempt to achieve a perfect de-convolution,which would reconstruct a signal exactly as it was before thedegradation. Instead, the attempt should be made to achieve somereasonable level of reconstruction that does not result in too large anamplification of the noise.

Before discussing the exemplary de-convolution methods utilized inprocessing an image acquired after deforming the optical wave front oflight from an object to achieve an EDF, it may be useful to firstdiscuss the spatial resolution and depth of focus in optical systems.Diffraction causes a point source of light to spread out when imaged byan optical system. The resulting intensity pattern, which is called anAiry disk, appears as a bright central spot surrounded by a series ofalternating light and dark rings. The intensity pattern is a projectionof the PSF of the optical system onto a flat plane. A PSF that producesan Airy disk having a smaller diameter and most of its energyconcentrated within the central spot results in a higher spatialresolution. As objects move from the best plane of focus, the Airy diskdiameter increases, and the energy spreads out into secondary andtertiary rings, covering a larger area, resulting in relatively poorerspatial resolution. At best focus, the radius (δ) of the central brightspot of the Airy disk is a function the numerical aperture (NA) of theoptical system and the wavelength (λ) of light comprising the image, asdefined by the following equation:

$\begin{matrix}{\delta = {\frac{0.62\; \lambda}{N\; A}.}} & (6)\end{matrix}$

The classical depth of field Δ of an optical system varies inversely asthe square of the numerical aperture as defined by the followingequation:

$\begin{matrix}{\Delta = {\pm {\frac{0.5\; \lambda}{N\; A^{2}}.}}} & (7)\end{matrix}$

For a typical moderately high-resolution objective (0.75 NA) used in thecenter of the visible spectrum (550 nm), the diffraction limitedresolution and the depth of focus as defined by Equations 6 and 7 are0.45 microns and +/−0.49 microns, respectively. As illustrated in FIG.8, the process of imaging is the mathematical equivalent of convolution.The spatial and intensity information contained within the object (250line pairs/mm bar target) as shown in the leftmost portion of FIG. 8 isconvolved with the PSF of the optical system, resulting in the imageshown in the rightmost portion of FIG. 8. The image appears very similarto the object, but some contrast is lost and the edges of the bars arenot as sharp as in the original object. This result is caused by thesignal content in the original object being spread out due to the PSF ofthe optical system. The lower thumbnail images in FIG. 9 demonstrate theeffect of defocus on both the PSF and the resulting imagery as the focuschanges. At 1μ (micron) of defocus, blurring becomes evident and by 4μof defocus, the optical system has lost the ability to resolve theindividual bars in the target. By 8μ of defocus, the bar target isunrecognizable and suffers significantly diminished intensity.Accordingly, when imaged by a 0.75 NA optical system, a cellular featuresuch as a FISH spot having an area of less than one micron and locatedsix microns away from the plane of best focus will blur into an areacovering more than 100 microns, rendering it unrecognizable to a humanobserver and making automated detection and enumeration difficult atbest. This result can occur when viewing FISH probes located at theperiphery of the nucleus.

Confocal image stacking techniques avoid this problem by synthesizing animage of the cell with all features simultaneously in focus via thecollection of multiple images of the cell at different focal planes. Ateach focal position, an image is collected by scanning a spot ofillumination over the object with a conjugate pinhole located at anintermediate image plane in the collection system. The conjugate pinholesubstantially eliminates light from objects outside the focal plane,providing a crisp image of the object structures in the immediate focalplane. By applying image reconstruction algorithms to the stack ofimagery, a high-resolution composite image can be generated with theentire cell in focus on a single plane.

As discussed above, the convolution process inherent in imaging can be“undone” through post-processing of the image using de-convolution. Thiseffect can be visually illustrated by reversing the process shown inFIG. 8, where the PSF can be “removed” via de-convolution from the imagein the rightmost portion of FIG. 8, such that the image appears morelike that of the actual object (the leftmost portion of FIG. 8). Withgood foreknowledge of the PSF, de-convolution algorithms can be appliedto an image to minimize the effect of optical system performancelimitations, resulting in a better representation of the originalspatial and intensity content of the object. This process works wellwhere there is a high signal-to-noise ratio in the image, and the objectis a two-dimensional planar structure with very little depth along theoptic axis, such as a semiconductor photo-mask, a printed page, or thebar target shown in FIG. 8. However, in cell analysis applications, theobjects being analyzed are inherently 3-D with respect to the depth offield of the optical system. The resulting image of a cell on a detectoris composed of many different degrees of point spread depending upon thelocation of a particular cell structure or probe, with respect to theplane of best focus. The presence of multiple PSFs within the imagesubstantially impairs the de-convolution process. Notwithstanding, itshould be noted that 3-D de-convolution of multiple PSFs has beensuccessfully applied to image stacks from standard fluorescencemicroscopes; however, the process still requires the collection ofmultiple images of the same cell taken at various positions along theoptical axis.

Evaluation of EDF Methods & De-Convolution using Modulation TransferFunctions

A convenient method to theoretically evaluate the expected performanceof the various EDF methods described above (WFC EDF, SphericalAberration EDF, and TOPTDI EDF) is to compare their modulation transferfunctions (MTF). The typical MTF plot provides a quantitative assessmentof contrast over a range of spatial frequencies. For the comparison ofthe EDF methods discussed above, a single spatial frequency was chosen,and curves were generated for different focus positions. A through-focusMTF plot shows the behavior of the decreasing contrast function oneither side of the best focus position. The exemplary flow imagingsystem utilizes a pixel size of 18 microns at the detector,corresponding to a maximum sampled spatial frequency of 27.8 linepairs/mm at the detector plane. The through-focus MTF plots werecalculated at approximately half the maximum resolvable spatialfrequency, or 14 line pairs/mm (500 line pairs/mm in object space), overa focal range of +/−10 microns in object space. The optimal performancefor an ideal system would be a flat response (i.e., a constant MTF) withmaximum contrast over the widest focal depth. FIGS. 10A and 10B show afamily of curves representing contrast versus focus for the various EDFmethods (without PSF de-convolution), as well as the non-EDF version ofthe exemplary imaging system.

As shown in FIG. 10A, the standard non-EDF system (solid line) providesthe best contrast at the plane of focus. However, the contrast falls offrapidly as the focal position changes. At 2.5 microns of defocus, thestandard system provides no contrast in the image. Numerous nullcontrast points are observed throughout the plotted focal range. TheTOPTDI (continuous long dash) EDF method integrates light from focalplanes over a range of −5 to +5 microns from best focus. At best focus,the contrast is about 0.2, which is less than one-third of the standardin-focus contrast, but the TOPTDI EDF contrast remains relativelyconstant over a much wider range of focal positions. The WFC EDF methodprovides slightly lower contrast than the TOPTDI EDF method, but with agreater enhancement to the depth of focus. The Spherical Aberration EDFmethod sacrifices more contrast than either of the other EDF methodsmodeled here, while providing less improvement to the depth of field. Italso exhibits a classical non-symmetrical behavior about the best focusposition. The lower plot in FIG. 10B illustrates a “modulationnormalized” view of the same data, which more clearly shows the relativedepth of field enhancements provided by each method.

FIGS. 11A and 12A show simulated point source imagery generated for thevarious EDF methods using collection parameters associated with theexemplary flow imaging system, including an 18 micron pixel size (0.5microns in object space), 0.75 counts of random noise per pixel, and thecorresponding PSFs for the various focus positions. FIG. 11B shows theresults of ten iterations of a Richardson-Lucy de-convolution algorithmapplied to each of the EDF images, using the best focus PSF as thede-convolution kernel. The peak intensity (based on a 10 bit A/Dconversion) for each thumbnail image is listed above each image. Asdemonstrated in the upper thumbnail images in FIG. 11B, the PSFde-convolution process can recover a high degree of image contrast (673counts for TOPTDI at 5 microns of defocus versus 801 counts at bestfocus in the non-EDF image). The display of each image is scaled forvisualization purposes, so that the brightest pixel in the image appearsblack, and the lowest intensity in the background appears white, causingthe background noise to appear higher in the cases where the PSF imageryhas a lower peak intensity, particularly in the case of standard imageryat five microns of defocus. It should be understood in all cases thenoise level in all pre-de-convolved imagery is the same.

The simulated imagery illustrates the effectiveness of both the TOPTDIEDF and WFC EDF methods in maintaining a constant PSF over an extendedfocal range. The results are particularly striking when comparing thede-convolved EDF imagery to the standard imagery at five microns ofdefocus. In FIG. 12A, the peak intensity in the standard image drops to19 counts at the defocus position, while both the TOPTDI EDF and WFC EDFmethods produce peak intensities in excess of 350 counts (FIG. 12B),resulting in an increase in contrast of more than 30 fold (340 countsvs. 9 counts) for both of these EDF methods (over standard imaging). Theimagery in the WFC EDF method exhibits some asymmetrical horizontal andvertical artifacts after processing. However, the artifacts areattenuated by more than an order of magnitude in comparison to theprimary image. Optimization of this first-generation WFC element andde-convolution kernel is expected to further reduce these artifacts. Theinduced spherical aberration method fares better under defocusconditions than the standard optical system, but exhibits much lowercontrast with defocus than the other two EDF methods: 151 counts (FIG.12B) vs. ˜350 counts (FIG. 12B).

Empirical Evaluation of the WFC EDF Method using Engineered Bead Samples

Simulation of the various EDF methodologies described above offeredinsights into the advantages and disadvantages of each of thealternative EDF methods. The WFC EDF method was chosen forimplementation in an EDF modified version of the empirical imagingsystem of FIG. 1A, based on its high level of performance in modeling,its flexibility in implementation, and because it offered the ability tocustom tailor the degree of depth of field extension to specificapplications by employing a choice of any one of multiple WFC elements,each having a different sag function.

To implement and empirically test the WFC method, a crossed cubic WFCelement was procured (available from CDM Optics, Inc., Boulder, Colo.)The element was installed at an external aperture stop in the exemplaryflow imaging system, and the PSF of the modified imaging system wasmeasured by running a sample of 200 nanometer diameter fluorescent beads(Invitrogen, FluoSpheres™ carboxylate-modified microspheres, 0.2 μm,yellow-green, 505/515 2% solids, F-8811), which was prepared at a10,000:1 dilution, and run on the modified flow imaging system. Suchbeads are sufficiently small relative to the pixel size and diffractionlimited spot size of the exemplary imaging systems optics so as to beconsidered as point sources. FIGS. 13A and 13B show a small sampling ofthe PSF imagery collected during the run. The form of the PSFcorresponds very closely to the modeled imagery shown in FIG. 11B.Approximately 1,000 bead images were collected and processed to generatethe composite PSF shown in FIG. 13B. Processing included a linearinterpolation of each image to remove shift variance caused byunder-sampling, and then spatially aligning each image such that thehighest intensity appeared in the same pixel for each image. A meanintensity was then calculated for each pixel to generate the compositePSF used in the subsequent image de-convolution step.

To further evaluate the exemplary flow imaging system with WFC EDFimaging, a simple test was devised using 2.5 micron diameter fluorescentbeads (as manufactured by Invitrogen Inc., Linear Flow Green), 0.1%intensity. A file was collected containing imagery from nine focuspositions spaced 2.0 microns apart. The exemplary flow imaging system'sauto-focus control was first enabled to establish the nominal best focusfor the beads. The auto-focus control was then disabled, and the stagewas positioned at −8.0 microns from best focus. Approximately 200objects were imaged in darkfield and fluorescence modes at each of thenine focus positions (−8, −6, −4, −2, 0, 2, 4, 6, and 8 microns frombest focus), resulting in a file containing 3,600 images over a panrange of 16 microns. Two test files were collected, one using standardimaging, and one using WFC EDF imaging.

FIGS. 14A and 14B show an image gallery of 8 pairs of consecutivelyselected beads (16 beads total) from each interval of the focus pan.Darkfield (blue) and fluorescence images (green) are shown for eachbead. A gallery of bead images collected using standard imagery areshown in FIG. 14A, and a gallery of bead images collected using WFC EDFimaging are shown in FIG. 14B. As is clearly apparent in FIG. 14B, theWFC EDF imagery maintains a much higher degree of focus over the panrange. Focus blur is present in the standard imagery (FIG. 14A) at +/−2microns of defocus in both darkfield and fluorescent images (objects701, 702, 1102, and 1103). At +/−4 microns of defocus, blurring issignificant (objects 500, 501, 1306, and 1307), and the bead imageryexhibits a marked decrease in peak intensity, as well as a large changein apparent area. By +/−8 microns of defocus, bead images (objects 100,101, 1707, and 1708) become difficult to discriminate from thebackground.

In marked contrast, the WFC EDF imagery of FIG. 14B maintains consistentimage characteristics throughout the focus pan with both the bead areaand intensity remaining relatively constant throughout the pan. Thisresult is particularly evident in the green fluorescent bead imageryshown in the right hand column of FIG. 14B (in a full color imagechannel 3 of FIG. 14B corresponds to green spectral images). There aresome artifacts present at higher levels of defocus in the form ofhorizontal and vertical lines emanating from the primary bead image anddirected toward the top and right hand side of the page. The artifactslargely resemble those generated in the simulation and exhibit muchlower intensity than the primary image. These artifacts are a result ofslight changes to the PSF with focus and can be minimized withoptimizations of the WFC element and de-convolution kernel. Modeling ofthe non-orthogonal nature of the artifacts has shown that they are alsodue in part to residual un-corrected spherical aberration in the opticalsystem. The darkfield imagery appears similar in nature to thefluorescence imagery; however, it exhibits stronger de-convolutionartifacts, especially at high levels of defocus. This result may be duein part to the fact that the de-convolution kernel was generated fromthe fluorescent imagery. Future optimizations will include channelspecific kernels, balancing of in focus and out of focus imagery forkernel generation, elimination of residual spherical aberration andoptimized WFC waveforms; each of which will reduce artifacts.

FIGS. 15A, 15B, 16A, and 16B provide a quantitative analysis of theentire image set from which the imagery in FIGS. 14A and 14B wasselected. In these Figures, the peak pixel intensity and area of eachobject are plotted against object number for both standard images (FIGS.15A and 15B), and EDF images (FIGS. 16A and 16B), where each dot in adot plot represents a single bead. A total of 1,800 objects were imaged,including approximately 200 objects acquired at each of nine focalpositions, with each focal position separated by 2 microns. Object #1and object #1800 are therefore spaced 16 microns apart, with the bestfocus position corresponding to object numbers in the range of800-1,000. The best focus position was gated using the regions “In Focuspk” or “Infocus Area,” with the accompanying mean values for the gateddata shown below the corresponding dot plot. In a similar manner, beadsfrom the +/−8 micron focus positions were also gated.

Referring to the dot plots of FIGS. 15A and 16A (i.e., the upper portionof each respective Figure), the dot plot for the standard image set (theupper portion of FIG. 15A) exhibited nearly a 14-fold decrease inaverage peak intensity (641 counts vs. 44 counts) between the best focusand the “8 um defocus” positions. In contrast the EDF dot plot (theupper portion of FIG. 16A) showed only approximately a 2-fold decreasein average peak intensity (613 counts vs. 287 counts) over the samefocus pan. Allowing for the increased focal range and the larger beadsize, these results were consistent with the theoretical models for thebehavior of peak intensity.

Referring to the dot plots of FIGS. 15B, and 16B (i.e., the upperportion of each respective Figure), the fluorescent EDF imagery of FIG.16B exhibited a consistent area of approximately 24 pixels throughoutmost of the focus range, rising to 32 pixels at the +8 micron defocusposition. In contrast, the dot plot of the standard imagery (the upperportion of FIG. 15B) exhibited an increase in area of almost 14 times,from 32 pixels to 437 pixels at −8 microns of defocus. Using the areaand peak intensity as figures of merit, the exemplary flow imagingsystem with WFC EDF imaging demonstrates 7-14 times better featureconsistency through a depth of field covering the majority of mostprokaryotic and eukaryotic cell diameters.

A statistical analysis of the noise contained in the imagery wasperformed by evaluating the standard deviation in background signaloutside the bead image for each individual object. An analysis of over2,100 objects for each focus pan indicates the median standard deviationin background signal is 0.97 and 1.30 counts, respectively, for thestandard and EDF focus pans (identified by σ in each of FIGS. 15A and16A). The increase in noise of 0.33 counts will degrade thesignal-to-noise ratio and therefore, negatively impact the sensitivityof the instrument. However, in comparison to standard imaging, thedegradation will be greatest for objects located at the best plane offocus. For objects located away from the best plane of focus, theincreased signal maintained via EDF should more than offset the increasein noise. Sensitivity studies of the standard exemplary flow imagingsystem demonstrate sensitivity superior to standard flow cytometry andindicate an ability to detect as little as 50 molecules of equivalentsoluble fluorescein. Further empirical studies of EDF imaging willinclude a detailed sensitivity study of the EDF collection mode.

Exemplary Post-Processing De-Convolution of Imagery

In this empirical study, imagery captured in the WFC EDF mode was postprocessed using a Richardson-Lucy (R-L) iterative de-convolutionalgorithm to restore fidelity. Starting with a good measurement of thePSF (as modified by the WFC element), the technique seeks to maximizethe likelihood of the de-convolved image by using the ExpectationMaximization (EM) algorithm. Specifically, it assumes an undistortedimage f which is convolved with a PSF h where n denotes the noiseassociated with the image. Then, EDF modified image g is given by thefollowing equation:

g=h{circle around (x)}f+n  (8)

where {circle around (x)}is the convolution operator. The R-L algorithmattempts to reconstruct f using the following relationship:

$\begin{matrix}{{\hat{f}}_{k + 1} = {{\hat{f}}_{k}\left( {h*\frac{g}{h \otimes {\hat{f}}_{k}}} \right)}} & (9)\end{matrix}$

and where {circumflex over (f)}_(k) is the estimate off after kiterations, and * is the correlation operator. Stability is maintainedand convergence achieved in 5 iterations by constraining {circumflexover (f)}_(k) to be nonnegative and by normalizing at every step toconserve energy between g and {circumflex over (f)}_(k).

Evaluation of Chromosome Enumeration Using Standard and EDF Imaging

FISH probes offer a powerful means for detecting and/or quantifyingRNA/DNA in a cell and/or cellular organelle. Current slide-based FISHprotocols require fixation (e.g., with a polar organic solvent such asmethanol) of intact cells. However, this fixation step is not compatiblewith in-suspension hybridization due to the occurrence of substantialcell loss and cell clumping. Fluorescence In Situ Hybridization-InSuspension (FISH-IS) protocols for performing chromosomal detection onwhole cells maintained in fluid suspension have therefore beendeveloped. These protocols enable the cells to be fixed and hybridizedwithout significant loss of cells or cell clumping. FISH-IS has beensuccessfully performed on many different cell types with a variety ofprobes that are of interest to the clinical and scientific researchcommunities.

Automated chromosome enumeration via FISH or FISH-IS probing is anapplication for which EDF imaging may confer significant benefits.Defocus causes significant changes in the presentation of probes oftenblurring one into another or spreading out the signal to such a degreethat it is difficult to automatically segment, or visually separate FISHprobes from each other or from non-specific binding in the nucleus.

To compare the efficacy of chromosome enumeration between the standardand extended depth of field configurations, cells of the Jurkat humanlymphoma line were grown in a suspension culture, then probed using aFISH-IS protocol. Cells were fixed and permeabilized with successiveincubations (5 minutes at 4° C.) in 30%, then 70% Carnoy's solution (3:1methanol:acetic acid) in phosphate buffered saline (PBS). Aftercentrifugation, cells were washed once in 2×SSC (a commonly used bufferincluding 3 M NaCl, 0.3 M NaCitrate, pH 7.0), then re-suspended in ahybridization buffer containing a Spectrum Green labeled chromosome 8enumeration probe, according to the manufacturer's directions (Vysis).To hybridize the probe, cells in PCR tubes were exposed to 80° C. for 5minutes and 42° C. for 2 hours in a DNA thermocycler. 100 ul of 2×SSCwas added to the tubes, and the cells were pelleted by centrifugation.The pellets were then re-suspended in 50 ul of 1% paraformaldehyde (inPBS). The sample was then loaded into the exemplary flow imaging system,and a file of 1,000 cells was collected in the standard collection mode(i.e., without the optical deformation element in place). A second filewas collected from the same sample immediately thereafter using the WFCEDF collection mode. Both files were analyzed in the same manner usingIDEAS™ software to detect and enumerate chromosome 8 in each cell. Imagegalleries were generated of cells having one, two, or more copies ofchromosome 8. The entire collection time for both files was severalminutes (including the time required to switch from standard to EDFmodes).

The results were automatically analyzed to enumerate copies of the Ychromosome in each cell. Simple classifiers using brightfield imagerywere developed to exclude cellular debris, doublet events, and otherartifacts from the analysis. A specialized segmentation routine andconnected components analysis were performed on the fluorescence imageryto generate a first pass enumeration of chromosomes on single cells. Arefinement of the monosomy and disomy classified cells from the firstpass enumeration was performed to eliminate false positive events. Afterthe final classification step, the resulting imagery was manuallyreviewed to qualitatively judge the efficacy of the finalclassification. This analysis was not intended to be a rigorousexamination of the efficacy of the exemplary flow imaging system withEDF for chromosome enumeration. Rather, this experiment was performed toexplore an application for which the exemplary flow imaging system withWFC EDF imaging may have a beneficial result.

FIGS. 17A-23D present a brief overview of the analysis of these twofiles (standard images and EDF images). FIGS. 17A and 17B shows asampling of 20 cells (10 in each collection mode, i.e., FIG. 17Aincludes 10 cells obtained using standard imaging and FIG. 17B includes10 cells obtained using WFC EDF imaging), highlighting some of thechallenges in the classification of disomies within the Jurkat sample.The FISH-IS probe imagery is superimposed over a reduced contrastbrightfield image of the cells (black and white have been reversed toreduce the amount of black in the image, to facilitate reproduction inthis patent application) to provide a sense of scale and verify that theprobes are located within the cell. In FIG. 17A (the cell imagesobtained using standard imaging), at least one of the FISH-IS probes ispositioned out of the plane of focus. Consequently, the area of the outof focus probe increases and sometimes engulfs the second probe in thecell. Like the bead imagery shown in FIGS. 14A and 14B, the intensityfalls off significantly with defocus, making it difficult toautomatically segment the probe or even see it in the image. Image 916of FIG. 17A includes a cell in which two probes appear to be in closeproximity. Slight defocus may have caused these relatively bright probeimages to blur into each other, creating what appears to be a singlelarge probe. Although it cannot be specified with certainty, this cellis thought to have two probes due to the total intensity of the probesignal and the elongated shape of the probe. In marked contrast, the EDFimagery presented in FIG. 17B, shows discrete FISH-IS spots even whenthey are positioned in close proximity to each other, as in images 298and 935. Unlike the standard collection mode of FIG. 17A, the EDFimagery of FIG. 17B exhibits little to no blurring of FISH-IS spots.This result is also readily apparent when comparing the larger selectionof images shown in FIGS. 22A-23D, wherein each FISH labeled chromosomeappears as a bright, tightly focused spot.

Development of FISH Spot Enumeration Classifier and ClassificationResults

In order to determine the efficacy of EDF imaging on the enumeration ofchromosomes, an exemplary, simple five-step classifier was developedusing the IDEAS™ analysis software. The first two steps involvedsegmentation and the selection of appropriate objects within the datafile for subsequent analysis (the data file includes each imagecollected from a sample of cells or objects run through the flow imagingsystem). Object selection was accomplished by plotting the brightfieldaspect ratio vs. brightfield area, as shown in the dot plot in FIG. 18.A gate 156 was drawn that encompassed primarily single cells (image 424being exemplary of a cell in the gated region) and excluded cellfragments/debris (image 845 being exemplary of a cell fragment ordebris), and grouped cells (image 75 being exemplary of a grouping orcluster of cells). The gate defined a population named “Cells”containing 595 individual objects, to which subsequent analysis wasapplied. A similar segmentation and selection process was performed onthe standard collection file (i.e., images of cells collected withoutusing EDF imaging) and resulted in 588 individual objects.

The third step in classification (graphically illustrated in FIGS.19A-19C), involved refinement of the standard segmentation mask toisolate areas of local maxima in each fluorescence cell image. Afluorescence image 89 of a cell, collected in Channel 3, is shown priorto segmentation in FIG. 19A, after initial segmentation (light blueoverlay) to identify all areas containing light above background in FIG.19B, and after morphology segmentation in FIG. 19C (light blue overlay).Morphology masking is a form of contour masking to identify areas oflocal maxima contained in the initial segmentation mask.

The fourth step in the exemplary classification employed an IDEAS™feature called “FISH Spots,” which uses the morphology mask to perform aconnected components analysis to enumerate discrete FISH spots containedwithin each fluorescent image. The results of this computation and thefinal gating of disomic cells, the fifth step in the classification, areshown in FIG. 20 for normal images, and in FIG. 21 for EDF images. Theupper leftmost portion of FIGS. 20 and 21 respectively correspond toFISH spot enumeration histograms for normal images and EDF images. Thefirst pass analysis using the standard collection mode yieldedenumerations of 506 monosomic, 67 disomic, and 15 polysomic (three ormore FISH spots) cells as shown in the histogram of FIG. 20 (theleftmost portion of the Figure). In contrast, the first pass enumerationwith EDF imaging yielded 421 monosomic, 136 disomic, and 38 polysomiccells, as shown in the histogram of FIG. 21 (the leftmost portion of theFigure). The EDF collection mode therefore produced a 2 times increasein the number of disomy and polysomy-classified cells, with a 17%decrease in monosomic cells. Manual review of the monosomy anddisomy-classified cells in both collection modes revealed a significantnumber of false classifications where hybridization had failed, leavingonly non-specific binding of the FISH-IS probes within the nucleus.

To improve classification accuracy, each population of monosomy anddisomy-classified cells was further analyzed by plotting peak intensityvs. area for the fluorescence channel. Non-specific binding generallyhas low peak intensity and large area, and therefore, plots of peakintensity vs. area improve discrimination of nonspecific binding events.Bi-variant plots of this analysis are shown in the middle portion ofFIGS. 20 and 21, for standard images and EDF images, respectively. Thediscrimination boundaries for the standard collection mode are notclear. This result is most evident in a boundary 201 (upper centerportion of FIG. 20) drawn to discriminate true and false positives fordisomy refinement. The boundary is complex and arbitrary and thereforeunsuitable for fully automated classification. In contrast, a boundary203 (upper center portion of FIG. 21) drawn for the EDF analysis isclear, with the true and false positive populations showing excellentseparation. Minor shifts in feature values due to preparationdifferences or instrument variations will not significantly affect theresults of the classifications, making these features and boundariessuitable for fully automated classification. The refined classificationsresult in 45 (the table in the rightmost portion of FIG. 20) and 96 (thetable in the rightmost portion of FIG. 21) disomy events for thestandard and EDF collection modes, respectively and a respective 191(the table in the center portion of FIG. 20) and 189 (the table in thecenter portion of FIG. 21) monosomy events.

FIGS. 22A-22D display a random set of images from each set of “Refined”and “False Positive” populations defined in FIG. 20 (i.e., standardimages). Images in FIG. 22A correspond to standard images of cellscategorized as Monosomy Refined in the center plot of FIG. 20. Images inFIG. 22B correspond to standard images of cells categorized as MonosomyFalse Positive in the center plot of FIG. 20. Images in FIG. 22Ccorrespond to standard images of cells categorized as Disomy Refined inthe center plot of FIG. 20. Images in FIG. 22D correspond to standardimages of cells categorized as Disomy False Positive in the center plotof FIG. 20.

FIGS. 23A-23D display a random set of images from each set of “Refined”and “False Positive” populations defined in FIG. 21 (i.e., standardimages). Images in FIG. 23A correspond to EDF images of cellscategorized as Monosomy Refined in the center plot of FIG. 21. Images inFIG. 23B correspond to EDF images of cells categorized as Monosomy FalsePositive in the center plot of FIG. 21. Images in FIG. 23C correspond toEDF images of cells categorized as Disomy Refined in the center plot ofFIG. 21. Images in FIG. 23D correspond to EDF images of cellscategorized as Disomy False Positive in the center plot of FIG. 21.

A review of the imagery in FIGS. 22A-23D sheds light on why the EDFcollection mode exhibits a two-fold increase in discrimination ofdisomic events. First, the EDF collection mode largely eliminated focusvariation, producing small, bright, tightly focused spots for eachhybridization event, as evident in both “Refined” monosomy and disomypopulations (FIGS. 23A and 23C). Second, these tightly focused spotsdramatically improved the performance of the morphological segmentationalgorithm and final classification steps by forming a clear demarcationbetween well-hybridized probes and non-specific binding events (theplots in the center and rightmost portions of FIG. 21, respectively).The false positive events shown in the galleries of FIGS. 23B and 23Dare a result of non-specific binding and result in large segmentationmasks with low peak intensities. The use of peak intensity and FISH Spotarea effectively discriminates false positive events. By contrast, it isvery difficult to discriminate between non-specific binding and highlydefocused probes as shown in FIGS. 23B and 23D. Third, by eliminatingfocus variation, probes located away from the ideal focal plane stillappear as small spots, which is in contrast to the probe imagery foundin images 213, 228, 245, 255, 257, 275, etc. shown in FIG. 22A or images15, 251, 279, 465, and 624 etc. of FIG. 22C. Tight focus substantiallyreduces the probability of events where a defocused probe image engulfsor contacts a second probe image in the cell. With standard imaging, itis a rarity to find imagery similar to images 55 and 247 of FIG. 23C,where two probes are in close proximity and tightly focused. More likelythan not, one of these probes will blur, engulfing the other, leading toa misclassification of a disomic event as a monosomic event.

It is likely that future optimizations of the exemplary flow imagingsystem with extended depth of field will provide for furtherimprovements in image quality and advanced capabilities. Since theexemplary flow imaging system collects imagery in a flow cuvette withimage collection access to all four sides of the cell, unlikeslide-based imaging systems, there exists the potential to develop atwo-axis orthogonal implementation of the architecture described herein.Coupling a two-axis version of the exemplary flow imaging systemarchitecture (i.e., a flow imaging system such as that shown in FIG. 2)with the EDF techniques discussed above would provide a means to performfull 3-D cell mapping and optical sectioning similar to confocaltechniques, but at two to three orders of magnitude greater speed andwithout photo-bleaching. Each axis would collect an EDF projection ofthe cell from orthogonal perspectives, enabling a 3-D reconstruction ofthe cell, as is done in optical tomographic methods. However, unlikeconfocal techniques, this method would provide an isometric perspectivewith consistent resolution in all axes. Since the cells would be mappedin a single pass, photo-bleaching would be minimized and, withsufficient image processing capacity, tens of thousands of cells couldbe analyzed in several minutes. FIG. 2 schematically illustrates such astereoscopic imaging system.

The high-resolution EDF flow imaging techniques disclosed herein shouldfind beneficial application in the following types of image-basedanalytical studies: (1) FISH-IS, which provides high throughputautomated spot counting of FISH-probed cells in suspension; (2) CellCycle and Mitosis Analysis for quantization and visualization ofDNA-stained cells; (3) Stem Cell Imaging for visualization of rarecells; (4) Phagocytosis for quantitative analysis of macrophageactivity; and (5) Cell Signaling for imaging and quantization ofT-cell/antigen-presenting cell conjugates. Moreover, one of the mostpromising applications is the high throughput genetic testing of cellsusing FISH-IS cell probing technique. Standard FISH is increasinglybeing used for such purposes as prenatal genetic testing, qualifyingpatients for breast cancer treatment with Herceptin™, and leukemialymphoma testing. Current methods of FISH probing are typicallyperformed manually on a small number of cells per test, which makes themunsuitable for identifying and classifying cancer or other target cellsthat may be present at less than five percent of the sample. The FISH-IStechnique, in connection with the exemplary EDF flow imaging system'sability to analyze tens of thousands of cells, will allow the detectionof rare target cells for clinical applications like cancer detection aswell as the correlation of genetic and phenotypic traits in targetvalidation studies.

Further improvements relate to optimizing the PSF used for imagereconstruction. More specifically, a custom model PSF for each channelwill be created, to take into account different focal depths andaberrations which may be present at different wavelengths. Thus,different correct PSFs will be used for post image processing (i.e.,image de-convolution). Such PSFs will be tailored to work with a givendepth of field, by collecting data from beads over the full depth forwhich the system is expected to perform.

Exemplary Computing Environment

As discussed above, a key aspect of the EDF imaging techniques disclosedherein involves post image acquisition processing to enhance the imagedata, to achieve an EDF image. Such image processing corrects for errorsintroduced by the PSF of the imaging system, and the intentionaldistortion of the optical wave front from the object. Preferably, suchimage processing is a de-convolution process based on the PSF of theimaging system (or other corrective PSFs, generally as discussedimmediately above). FIG. 24 schematically illustrates an exemplarycomputing system 250 suitable for use in implementing the method of FIG.4 (i.e., for executing step 170 of this method). Exemplary computingsystem 250 includes a processing unit 254 that is functionally coupledto an input device 252 and to an output device 262, e.g., a display(which can be used to output a result to a user, although such a resultcan also be stored). Processing unit 254 comprises, for example, acentral processing unit (CPU) 258 that executes machine instructions forcarrying out an analysis of data collected in connection with operationof the vehicle to determine upon which one of the plurality ofpredefined routes the vehicle has been operated in conjunction withacquisition of the data. The machine instructions implement functionsgenerally consistent with those described above with respect to step 170of FIG. 4, as well as those at other locations herein with respect toimage processing to enhance the EDF image. CPUs suitable for thispurpose are readily available, for example, from Intel Corporation, AMDCorporation, Motorola Corporation, and other sources, as will be wellknown to those of ordinary skill in this art.

Also included in processing unit 254 are a random access memory (RAM)256 and non-volatile memory 260, which can include read only memory(ROM) and may include some form of memory storage, such as a hard drive,an optical disk (and drive), etc. These memory devices arebi-directionally coupled to CPU 258. Such storage devices are well knownin the art. Machine instructions and data are temporarily loaded intoRAM 256 from non-volatile memory 260. Also stored in the memory are anoperating system software and ancillary software. While not separatelyshown, it will be understood that a generally conventional power supplywill be included to provide electrical power at a voltage and currentlevel appropriate to energize the components of computing system 250.

Input device 252 can be any device or mechanism that facilitates userinput into the operating environment, including, but not limited to, oneor more of a mouse or other pointing device, a keyboard, a microphone, amodem, or other input device. In general, the input device will be usedto initially configure computing system 250, to achieve the desiredprocessing (e.g., to process image data to produce images as discussedabove). Configuration of computing system 250 to achieve the desiredprocessing includes the steps of loading appropriate processing softwareinto non-volatile memory 260, and launching the processing application(e.g., loading the processing software into RAM 256 for execution by theCPU) so that the processing application is ready for use. Output device262 generally includes any device that produces output information, butwill most typically comprise a monitor or computer display designed forhuman visual perception of output. Use of a conventional computerkeyboard for input device 252 and a computer display for output device262 should be considered as exemplary, rather than as limiting on thescope of this system. Data link 264 is configured to enable image datacollected from a flow imaging system to be introduced into computingsystem 250 for subsequent image processing as discussed above. Those ofordinary skill in the art will readily recognize that many types of datalinks can be implemented, including, but not limited to, universalserial bus (USB) ports, parallel ports, serial ports, inputs configuredto couple with portable memory storage devices, FireWire (conforming toI.E.E.E. 1394 specification) ports, infrared data ports, wireless dataports such as Bluetooth™, network connections such as Ethernet ports,and Internet connections.

Although the concepts disclosed herein have been described in connectionwith the exemplary form of practicing them and modifications thereto,those of ordinary skill in the art will understand that many othermodifications can be made thereto within the scope of the claims thatfollow. Accordingly, it is not intended that the scope of these conceptsin any way be limited by the above description, but instead bedetermined entirely by reference to the claims that follow.

1. A method for producing an extended depth of field image of an object,comprising the steps of: (a) deforming an optical wave front of lightfrom the object to produce modified light, such that a point spreadfunction (PSF) of an imaging system used to collect the modified lightis substantially invariant across the extended depth of field; (b)dispersing the modified light, producing dispersed light; (c) focusingthe dispersed light to produce at least one dispersed image, thedispersed image being formed by light simultaneously collected from aplurality of different focal planes in the extended depth of field; (d)detecting the dispersed image of the object to generate image data; and(e) processing the image data to reduce artifacts introduced bydeforming the optical wave front, to produce the extended depth of fieldimage of the object.
 2. The method of claim 1, further comprising thestep of analyzing the extended depth of field image of the object todetermine at least one characteristic of the object.
 3. The method ofclaim 1, wherein there is relative motion between the object and animaging system used to produce the extended depth of field image of theobject.
 4. The method of claim 3, wherein the object in entrained in aflow of fluid.
 5. The method of claim 1, wherein the extended depth offield comprises less than about fifteen microns.
 6. The method of claim1, wherein the step of processing the image data comprises the steps of:(a) determining the PSF of the imaging system configured to deform theoptical wave front; and (b) using the PSF function to produce theextended depth of field image of the object.
 7. The method of claim 1,wherein processing the image data comprises the step of de-convolvingthe image data.
 8. The method of claim 7, wherein the step ofde-convolving the image data reduces spatial broadening and contrastloss induced by the step of deforming the optical wave front.
 9. Themethod of claim 1, wherein the step of deforming the optical wave frontcomprises the step of using an optical element to deform the opticalwave front.
 10. The method of claim 9, wherein the optical elementcomprises at least one element selected from the group consistingessentially of: (a) a phase plate configured to induce a phase deviationin the optical wave front; (b) an optical element configured to induce aspherical aberration in light received from the object; and (c) acuvette having different optical thicknesses at different locations,such that imaging through the different locations of the cuvette inducesdifferent degrees of wave front deformation.
 11. The method of claim 1,wherein the step of deforming the optical wave front comprises the stepof modifying the aberration correction of an objective lens.
 12. Amethod for producing an extended depth of field image of an object,while there is relative motion between the object and an imaging systemused to produce the extended depth of field image of the object,comprising the steps of: (a) using an optical element to induce anaberration in an optical wave front of light from the object to producemodified light, such that a point spread function (PSF) of an imagingsystem as modified by the optical element is substantially invariantacross the extended depth of field; (b) focusing the modified light toproduce an image of the object that includes light simultaneouslycollected from a plurality of different focal planes in the extendeddepth of field; (c) detecting the image of the object to generate imagedata; and (d) processing the image data to reduce artifacts introducedby deforming the optical wave front, to produce the extended depth offield image of the object.
 13. The method of claim 12, wherein the stepof detecting the image comprises the step of using a time delayintegration detector to collect the image over a period of time, whilethe object moves relative to the imaging system.
 14. The method of claim12, further comprising the step of dispersing the modified light into aplurality of light beams, such that: (a) the step of focusing themodified light comprises the step of focusing each of the light beams toproduce a respective image corresponding to that light beam, eachrespective image being formed from the modified light simultaneouslycollected from the plurality of different focal planes in the extendeddepth of field; (b) the step of detecting the image comprises the stepof detecting each respective image of the object to generate image data;and (c) the step of processing the image comprises the step ofprocessing the image data for each respective image to reduce artifactsintroduced by deforming the optical wave front, to produce the extendeddepth of field image of the object for each respective image.
 15. Themethod of claim 14, further comprising the step of analyzing theextended depth of field image of the object for each respective image todetermine at least one characteristic of the object.
 16. The method ofclaim 14, wherein the step of processing the image data comprises thesteps of: (a) determining the PSF of the imaging system as modified bythe optical element configured to deform the optical wave front; and (b)using the PSF function to de-convolve each respective image, therebyreducing spatial broadening and contrast loss induced by the PSF. 17.The method of claim 12, wherein the optical element comprises at leastone element selected from the group consisting essentially of: (a) aphase plate configured to induce a phase deviation in an optical wavefront; (b) an optical element configured to induce a sphericalaberration in light from the object; and (c) a cuvette having differentoptical thicknesses at different locations, such that imaging throughthe different locations of the cuvette induces different degrees of wavefront deformation.
 18. The method of claim 12, wherein the step ofdeforming the optical wave front comprises the step of modifying theaberration correction of an objective lens.
 19. An imaging systemadapted to perform extended depth of field imaging of an object,comprising: (a) an optical element configured to deform an optical wavefront of light from the object, such that a point spread function (PSF)of the imaging system as modified by the optical element issubstantially invariant across the extended depth of field; (b) acollection lens disposed so that light traveling from the object passesthrough the collection lens and travels along a collection path; (c) alight dispersing element disposed in the collection path so as todisperse the light that has passed through the collection lens,producing dispersed light; (d) an imaging lens disposed to receive thedispersed light, producing a dispersed image from the dispersed light;(e) a detector disposed to receive the dispersed image produced by theimaging lens, producing an output signal that is indicative of thedispersed image; and (f) a processor configured to manipulate the outputsignal to reduce artifacts introduced by the optical element configuredto deform the optical wave front of light from the object, to produce anextended depth of field image of the object.
 20. The system of claim 19,wherein the optical element comprises one element selected from thegroup consisting essentially of: (a) a phase plate configured to inducea phase deviation in an optical wave front; (b) an optical elementconfigured to induce a spherical aberration in light from the object;and (c) a cuvette having different optical thicknesses at differentlocations, such that imaging through the different locations of thecuvette induces different degrees of wave front deformation.
 21. Thesystem of claim 19, wherein the optical element configured to deform theoptical wave front of light from the object comprises an adjustableobjective lens, such that the aberration of the objective lens can bemodified to deform the optical wave front of light from the object. 22.The system of claim 19, wherein the optical element is selectivelypositionable, such that in a first position, the optical element deformsthe optical wave front, thereby enabling extended depth of fieldimaging, while in a second position, the optical element does not deformthe optical wave front, thereby enabling non-extended depth of fieldimaging.
 23. The system of claim 19, wherein the processor is configuredto use the PSF function as modified by the optical element tode-convolve the output signal, thereby reducing spatial broadening andcontrast loss induced by the PSF as modified by the optical element. 24.An imaging system adapted to perform extended depth of field imaging ofan object, while there is relative movement between the object and theimaging system, comprising: (a) an optical element configured to deforman optical wave front of light from the object, thereby producingmodified light, such that a point spread function (PSF) of the imagingsystem as modified by the optical element is substantially invariantacross the extended depth of field; (b) a collection lens disposed sothat modified light passes through the collection lens and travels alonga collection path; (c) a dispersing component disposed in the collectionpath so as to receive the light that has passed through the collectionlens, dispersing the light into a plurality of separate light beams,each light beam being directed away from the dispersing component in adifferent predetermined direction; (d) an imaging lens disposed toreceive the light beams from the dispersing component, producing aplurality of images, each image corresponding to one of the light beamsand being projected by the imaging lens toward a different predeterminedlocation; (e) a detector disposed to receive the plurality of imagesproduced by the imaging lens, producing an output signal that isindicative of imaging at the plurality of different focal planes; and(f) a processor configured to manipulate the output signal to reduceartifacts introduced by the optical element configured to deform theoptical wave front of light from the object, to produce an extendeddepth of field image of the object for at least one of the plurality ofimages.
 25. The system of claim 24, wherein the optical element is aphase plate configured to induce a phase deviation in the optical wavefront.
 26. The system of claim 25, wherein the phase plate is disposedproximate a numerical objective of the imaging system.
 27. The system ofclaim 24, wherein the optical element is configured to induce aspherical aberration in light from the object.
 28. The system of claim24, wherein the optical element is a cuvette having different opticalthicknesses at different locations, such that imaging through thedifferent locations of the cuvette induces different degrees of wavefront deformation.
 29. The system of claim 24, wherein the opticalelement is selectively positionable, such that in a first position, theoptical element deforms the optical wave front, thereby enablingextended depth of field imaging, while in a second position, the opticalelement does not deform the optical wave front, thereby enablingnon-extended depth of field imaging.